“VALUATION STUDY OF MANGROVE
PLANTATIONS ESTABLISHED Under Sindh Coastal Community Development Project (SCCDP)”
Akhtar A. Hai (Consultant-IUCN)
June 2013
International Union for Conservation of Nature, Pakistan
Table of Contents
EXECUTIVE SUMMARY
1. INTRODUCTION
2. LITERATURE REVIEW
2.1 International Evidences
2.2 Evidence from Indus Delta
2.3 Focus Group Discussion
3. BACKGROUND OF THE INDUS DELTA
4. SOCIO-ECONOMIC PROFILE OF THE RESPONDENTS
5. ECONOMIC VALUATION OF MANGROVES – METHODOLOGY
5.1 Estimating the Willingness to Pay
5.2 Economic Valuation of Mangroves - Empirical Valuation
5.2.1 Estimating Direct Values
5.2.2 Indirect Value
5.2.3 Non Use Value
5.3 Derivation of Total Value of Mangroves Forest
5.4 Comparative Estimates on Valuation of Mangroves
5.5 Distribution of Total Economic Benefits of Mangroves Annually
5.6 Derivation of Benefit Cost Ratio and IRR
CONCLUSIONS AND RECOMMENDATIONS
REFERENCES
ANNEXURE
Research Team
1. Mr. Akhtar A. Hai Development Economist & Team Leader
2. Dr. Ambreen Fatima Econometrician
3. Mr. Arsalan Ahmed Research Officer
4. Mr. Ali Rashad Research Officer
5. Mr. S. Qaisar Ali Anjum Project Secretary
(i)
EXECUTIVE SUMMARY
- The on-site (i.e. coastal environment) is interrelated with off-site (open sea
environment) and jointly appear as a great natural resource on which the
coastal communities depend heavily for their livelihood.
- The current state of economic and social development in coastal areas of
Sindh, is extremely poor. These communities remain isolated in receiving their
share in the economic development taking place in the country.
- The current situation in the Indus delta amply demonstrates the level of
dependence of coastal population on mangroves for their livelihood (directly
and indirectly).
- However, if such an exclusive dependence continues in the long run, it may be
productive or unproductive for mangroves based on how this great natural
resource is valued by the coastal communities. Such an understanding (or lack
of it) would be pivotal to the long run sustainability of mangroves in the
region.
- Internationally, awareness about the mangrove has been promoted through
number of studies, but a small number of studies estimated and identified the
economic value of mangrove ecosystems. Sathirathai (2000) studied for the
area of SuratThani, South of Thailand.
- Emerton, L., and Kekulandala (2003) found out the total economic value of
mangroves, in the region of Muthurajawela wetland in Sri Lanka,
asUS$ 7,567,604 per year.
- IUCN (2003) for Kala Oya in Sri Lanka shows the economic benefits of
mangrove ecosystems by adding up the direct and indirect benefits. The direct
use value of mangrove work out to be US$ 8,956/ha/year.
- For Pakistan, FAO, WWF, Forest Department and IUCN have conducted
studies for the assessment of mangroves area especially for the region of Indus
delta. These studies highlight that mangroves are serving as breeding grounds
for shrimp and fish species. Sindh Coastal Development Authority and other
organization had replanted about 80,000 ha of mangroves along the Sindh
coast since 1985.
- According to the IUCN (2003) in Sindh coastal area around 1,06,588 hectares
of land have been lost to sea intrusion since 1963, and this will increase
to1,33,235 in next ten year due to this sea intrusion. The estimated agriculture
losses for five years 1995-2000 due to sea intrusion was estimated around
Rs.265.7 million.
- A number of Focused Group Discussions (FGD’s) were conducted to
understand the community relationship with mangroves. According to the
participants the reasons behind the reduction are: reduced supply of sweet
water and sediments, over cutting of mangroves for sale of timber, fuel wood
and poles for housing. Participants also criticized decision of the government
about restriction on the Indus water flows at Kotri barrage in 1960 and held
that responsible for the reduction in mangroves cover.
(ii)
- The average family size of all sampled households was 11.27, where the
minimum of 10.44 was for Shah Bunder and maximum of 13.55 for Kharo
Chhan. It is interesting to note that in Shah Bunder where the average family
size was lowest (i.e. 10.44), the average number of males (i.e. 3.46) was
higher than the average number of females (i.e. 3.21) and the associated
average number of children was lowest.
- The levels of education (in terms of years completed) of the respondents
shows that nearly two-third of the 160 households had no education. The
information on highest level of education completed within the family, the
average number of those who completed 12 years or more was 3.69 for Kharo
Chhan, 3.65 for Shah Bunder and 3.4 for Keti Bunder.
- The scale of devastation in these coastal talukas as a result of continuous sea
intrusion has resulted in the loss of fertile agricultural land. Currently,
agricultural land ownership has reduced along the coastal belt of Indus delta.
Only a fraction of land holding is brought under cultivation owning to the fact
that the supply of fresh water has reduced considerably.
- The ownership of livestock was limited in the area. Only 58 households out of
160 (i.e. 36 percent) were keeping livestock. The raising of camels was
reported only by 10 households with 7 from Shah Bunder.
- The pattern of housing construction is similar across the talukas. The
proportion of pacca housing structure in Keti Bunder was twice the proportion
in Kharo Chhan and Shah Bunder. The fact that over 48 percent of houses
were established in huts provides ample evidence of poverty levels prevailing
in coastal areas.
- The situation of housing and provision of civic amenities in the coastal area of
Indus delta, so depicted, reveals extremely poor quality of life. Under this
scenario, it is expected that these coastal communities depend in part on the
non-timber forest products from mangroves to derive a number of direct and
indirect benefits for their livelihood.
- A common view of the area reflects the fact that Keti Bunder has retained its
historical location as well as has acted as a center for various developmental
activities despite facing a number of threats in the form of natural as well as
man made disasters. In contrast, Shah Bunder could not sustain the devastation
of sea cyclone of mid 1990’s and as a result its taluka headquarter was shifted
to another location in the upstream area, its population was scattered and as
such currently the location of Shah Bunder’s proper settlement is lost to
antiquity. As a consequence, Shah Bunder has yet not reversed its position
undermining its fisheries catch and marketing and other economic
development prospects.
- The fisheries as a source of income was highest in Keti Bunder where 29 out
of 40 households (72.5 percent) had it as primary occupation. In case of Kharo
Chhan it was 52.5 percent and in Shah Bunder it was 43.8 percent, of the
sampled households. The highest participation was in fisheries activities all
across.
- Over 90 percent of the respondents reported visiting mangroves either
exclusively to collect forest products like fuel wood, fodder, catching fish
crabs, shrimps, honey, herbs, poles for use in house construction, animal
(iii)
browsing, or to take rest and recreation while going towards open sea for
fishing.
- The highest number of visits to mangroves was reported by respondents of
Keti Bunder i.e. 11.38 visits per month. It can thus be argued that fishermen
(or coastal population) of Keti Bunder visits mangroves more frequently than
those visiting from other talukas.
- When inquired about changes in mangroves cover during the last 50 years or
so, a vast majority (nearly 90 percent) reported that the cover has reduced or
destroyed during this period. The respondents indicated different causes for
this destruction of mangroves. A vast majority (41.8 percent) regarded sea
intrusion and cyclone as the main cause of destruction. Out of 66 respondents,
50 were from Shah Bunder.
- When inquired about the reasons for improvements in mangrove, nearly two
thirds (i.e. 105 respondents) regarded new plantation and another 12.7 percent
regarded proper care of mangroves as the main factors behind the
improvements in mangroves cover. Only 10 respondents argued that no
change took place in the status of mangrove cover (Table 4.15(b)).
- Based on the responses of sampled households towards different socio-
economic aspects, it becomes clearer that local community heavily depends on
fisheries as their exclusive source of livelihood. The incomes are largely
generated from fishing whereas the non-fishing occupations generate over one
third of their incomes.
- The data obtained through primary survey for this study shows that wood
obtained from the mangroves forest is not only used by households for
domestic purpose (non-marketed) but also for commercial purpose as well.
Sale of fuel wood is also generating livelihood for the households (marketed).
Average value of the wood used as fuel domestically was worth Rs.795 per
month while the fuel wood marketed was worth Rs.549 per month.
- Sample survey also indicates huge economic dependence of household on
shrimps, crabs and shell fishes. On average households were earning
approximately Rs.20,175 per month (2997 from crabs + 13946 from shrimps +
3232 from shell fishes).
- The situation is not much different for sale of crab as well. People of Keti
Bunder were on average earning around Rs.5000 per month from the sale of
crab. People of KharoChhan reported were earning almost Rs.2600 per month
while the people of Shah Bunder were earning only Rs.2000 per month from
the sale of crab.
- As the fish catch in the Indus delta is highly dependent on the mangrove
ecosystem, the importance of mangrove in sustaining the productivity of
on-shore and off-shore fisheries cannot be ignored.
- On average, a household was willing to pay around Rs.2,518 per month for the
protection and development of mangrove forest. Keti Bunder being the more
economically developed taluka among the three talukas surveyed, shows that
each household was willing to pay around Rs.4,145 per month.
- The three talukas of Indus delta comprising 254,000 individuals, is supported
by mangroves economically as well as ecologically. Despite massive
(iv)
degradation during the last 70 years or so, caused by reduced flow of sweet
water and sediments to the deltaic region, and increased dumping of untreated
industrial effluents into the sea, the mangroves have sustained and shown
resilience to natural and manmade threats towards its existence.
- The flow of benefits (directly and indirectly) to local communities are
significant. This study tends to show those streams of benefits extended to
communities. The seemingly different streams of on-shore and off-shore
benefits are in fact parts of a natural and integrated system where mangroves
act as a conduit in diversifying the natural production system. In pure
economic terms mangroves act as a production function which yields multiple
products.
- The biodiversity established and sustained by mangroves are its critical
strength. However, this strength has been subjected to tests of intrigue and
innocence over time i.e. the situations when humans knowingly and
unknowingly exert pressures on this great natural resource for their short term
gains.
- The detailed household survey, consultations with stakeholder and available
literature, total value (both economic and non-economic) of mangroves was
computed. The values are represented net of costs incurred by the sampled
households. It portrays a total value of 3.27 Billion Rs. (US$ 32.7 Million) per
year for the whole region (i.e. aggregation of 3 talukas).
- The comparative figures for mangroves estimated for Thailand, Sri Lanka, and
Kenya during the last decade or so, reveal higher values for Pakistan’s
mangroves on Indus delta. Given the higher productivity of fish biomass in the
Arabian Sea in relation to the other oceans of the world, the higher levels of
Pakistan’s potentials not unexpected.
- The study has estimated detailed account of different products particularly
non-timber forest products collected from on-shore locations as well as fish
catches in the off-shore locations.
- The estimated levels seem high in relation to comparable locations in the
region of Asia and Africa. The high productivity potentials, in the Arabian Sea
given its biomass of fish which has highest productivity level in the world,
needs to be harnessed through modernization of the system of fish catch and
its re-generation, scientific processing and marketing in order that the export
potentials of marine products are enhanced, local employment is generated
and poverty levels are reduced.
- In addition to above the communities’ knowledge and interests towards
mangroves needs to been enhanced. Through development of eco-tourism in
the area the local community can participate with much bigger role towards
the sustenance of mangroves and the ecology.
- The socio-economic profiles of the coastal communities show significant
levels of social deprivation which is more severe than income poverty in the
area.
- Whereas the main source of livelihood of communities rests with fishing, their
dependence over mangrove forest in extracting direct and indirect benefits is
central to the overall living standards.
(v)
- The distinction between on-site and off-site activities also reveal the pivotal
and harmonious position mangroves play in extending flow of benefits within
the on-farm and off-farm areas.
- However, such an exclusive reliance on mangroves requires efforts to
conserve and develop mangroves which have long been affected by restricting
flow of sweet water and silt to the deltaic region.
- The historically reduced water supplies to the region and its impact on
mangroves when viewed in the context of all international conventions,
agreements and framework, establishes the right of the coastal communities
for compensation. It is suggested that if 0.10 percent of the annual value added
of Pakistan’s producing sectors (i.e. agricultural and manufacturing) is
allocated for the development and sustenance of mangroves and the coastal
communities of Indus delta, it would create a fund of Rs.10 billion annually.
- The economic analysis of the study reveals a benefit cost ratio of 3.56 which is
quite significant.
- The analysis also reveals an internal rate of return IRR of 25 percent which is
considered suitable for investments.
1
1. INTRODUCTION
This study focuses on the valuation of mangrove plantations established under Sindh
Coastal Community Development Project (SCCDP). It was carried out during the
period February-May, 2013 and was financed by ADB and administered by IUCN
Pakistan. It uses primary data, collected from three talukas (sub-Districts) of Thatta
District of Sindh namely Keti Bunder, Kharo Chhan and Shah Bunder, where
household survey of coastal communities and discussions with different stakeholders
(including Focus Group Discussion) were conducted to assess the local communities’
dependence on mangroves. It also uses literature and secondary data to cover
non-economic factors that impact on mangrove sustenance. In the process, the study
made estimates on different streams of benefits and costs (direct, indirect). In addition
to use values, non-use values were also computed e.g. willingness to participate (in
mangrove plantation) was also computed.
The on-site (i.e. coastal environment) is interrelated with off-site (open sea
environment) and jointly appear as a great natural resource on which the coastal
communities depend heavily for their livelihood. The current state of economic and
social development in coastal areas of Sindh, is extremely poor. These communities
remain isolated in receiving their share in the economic development taking place in
the country. In real term, the inhabitants of coastal areas of Indus delta have
continuously paid heavy cost in terms of the after effects of irrigation/agricultural and
industrial development in the rest of the country. The cost could easily be observed in
terms of reduced flow of sweat water and sediments to the delta, and untreated
effluents of the industrial and trading activities thrown into the delta have jointly put
adverse effects on the sustenance of mangroves.
Given the fact that the coastal areas have roundly been threatened by this perplex
situation where the flows of sweet water and sediments have been reduced, and flows
of untreated effluent from industrial sector have increased, a reversal in the pattern of
flows is required for the overall stability of the coastal area. Thus the damages to the
coastal ecology were doubled whereas the level of compensation in terms of improved
resettlement of affecties, stabilization of mangroves eco-system and improved living
environment for the inhabitants were not given any serious attention. A precise
estimate suggest that even 0.1 percent of the current value added of the producing
sector of Pakistan (i.e. Manufacturing and Agricultural sectors) is allocated towards
development of these coastal areas, particularly in the Indus delta which has been
primarily affected and where 95 percent Pakistan’s mangrove forests are located, the
resulting amount is around Rs.10 billion annually. Such an allocation could be used in
programmes aimed at conserving mangroves through replanting of forest, appropriate
treatment of industrial effluent, desalination plants, use of wind and solar energy and
development of marine fisheries. These developmental efforts could, at least in part,
compensate for the loss the local people and natural habitat have been incurring as a
result of irrigation and industrial sectors development in the upstream over time. The
current situation in the Indus delta amply demonstrates the level of dependence of
coastal population on mangroves for their livelihood (directly and indirectly).
However, if such an exclusive dependence continues in the long run, it may be
productive or unproductive for mangroves based on how this great natural resource is
2
valued by the coastal communities. Such an understanding (or lack of it) would be
pivotal to the long run sustainability of mangroves in the region.
In this back drop, this study focuses on estimating valuation of mangroves in the Indus
delta. The stream of benefits extended by mangroves (directly and indirectly) in the
coastal and off shore areas, as well as those common benefits and costs which cannot
be attributed at individual level, have been included in the estimation of valuation of
mangroves.
3
2. LITERATURE REVIEW
The available literature on the socio-economic aspects of mangrove forest is far and
few. In this section we have provided evidences from both international and nationally
available perspective – mostly on Indus delta.
2.1 International Evidences
Internationally, awareness about the mangrove has been promoted through number of
studies, but a small number of studies estimated and identified the economic value of
mangrove ecosystems. Sathirathai (2000) studied for the area of SuratThani, South of
Thailand. He estimated the total economic value of mangroves as US$ 1,422.48 per
household per year for the area which consists of 1,120 ha of mangroves. According
to the study the net returns from off shore is US$ 8.99/ha/year from mangroves. Also
the value of shoreline protection estimated approximately to
US$ 4,778.66(US$ 239/ha/year).
Emerton, L., and Kekulandala (2003) found out the total economic value of
mangroves, in the region of Muthurajawela wetland in Sri Lanka, asUS$ 7,567,604
per year. The study has divided the economic value of mangroves into flood
attenuation (5,057,396US$), industrial waste water treatment (US$ 1,690,729)
agricultural production (US$ 315,521), support to downstream fisheries
(US$208,333), firewood (US$ 82,917), fishing (US$65,208), leisure and recreation
(US$ 55,000), domestic sewage treatment (US$ 45,000), freshwater supplies for local
populations (US$ 39,375) and carbon sequestration (US$ 8,125).
IUCN (2003) for Kala Oya in Sri Lanka shows the economic benefits of mangrove
ecosystems by adding up the direct and indirect benefits. The direct use value of
mangrove work out to be US$ 8,956/ha/year. The value of mangroves in reducing the
pollution is estimated at Rs.552,960/year. The study also estimated Rs.20 Million as
the shore line protection value, Rs.11.27 million as carbon sequestration value,
Rs.813,930 in terms of flood water control, Rs.193,450 for sea intrusion value. The
government authorities of Kala Oya in Srilank also calculated the value of mangrove
ecosystem at Rs.215,434,350.
IUCN (2007) studied the economic value of mangroves through benefits availed from
the mangroves (fish, shrimp and fuel wood etc). According to the study the total
economic value was Rs.119,438 (US$ 1,171) per household per year. The direct use
of mangrove products (gross value) per household was Rs.9,953 per month. The study
also revealed that the total benefits availed by poor, medium and high income
households were 42 %, 37% and 21%, respectively. The value of mangroves as sea
protective barrier was US$ 392.5/ha and for fish breeding functions it was US$ 1,
77.9 to US$ 474.3/hectare.
United Nations Environment Programme (UNEP) study of 2011 for the region of
Gazi Bay, Kenya to estimate the economic valuation of mangroves in that area
(spread over 620 hectares). The study had included many direct and indirect uses of
mangroves and estimated the economic value for each benefit, by summing all. It
gives the total economic value of US $1,092.30. According to the study, the economic
value derived from mangroves included; fishery (US$ 44.00), wood (US$ 20.80),
4
apiculture (US$ 14.70), aquaculture (US$ 4.80), education &research (US$ 184.40),
tourism/recreation (US$6.50), carbon sequestration (US$ 126.00), shoreline
protection (US$91.70), biodiversity value (US$ 5.00) and existence value
(US$ 594.40).
Patrik (1999) studied the ecological basis for economic value of seafood production
supported by mangrove ecosystems. According to the study the annual market value
of fisheries (that use mangroves as habitat) per hectare of mangroves ranges from
US$750 to 11280. Gujja (1996) showed that the mangroves worked as life-support
systems for sustaining mollusk, fish, and shrimp aquaculture. Robertson (1992)
reviewed some other function of mangroves such as supply of organic carbon and
nutrients near the shore line by the litter (leaves) of mangroves. An estimate shows
that the dissolved material fluxes between mangroves and near shore areas was
379 kg/ha/year.
2.2 Evidence from Indus Delta
For Pakistan, FAO, WWF, Forest Department and IUCN have conducted studies for
the assessment of mangroves area especially for the region of Indus delta. These
studies highlight that mangroves are serving as breeding grounds for shrimp and fish
species. Sindh Coastal Development Authority and other organization had replanted
about 80,000 ha of mangroves along the Sindh coast since 1985. According to Baig
(2010) per hectare value of mangroves in Pakistan exceed to US$8,000. Shamsul
(2012) studied that around 200 fish species are found in the Indus delta region and
these mangroves provide a natural habitat to these fish species. He estimated
economic value of mangrove around US$ 750 to 16750 per hectare for annual
production of marine fish/shrimps. Shamsul (2012) also showed that the mangroves
are important for the shore line protection. According to the study on 20 May 1999 a
sea cyclone killed 6,200 people after making landfall at Shah Bunder. Mangroves can
reduce these losses by providing the supportive barrier against tsunami.
Other important benefit of the mangroves is that it protects the land from sea
intrusion. According to the IUCN (2003) in Sindh coastal area around 1,06,588
hectares of land have been lost to sea intrusion since 1963, and this will increase
to1,33,235 in next ten year due to this sea intrusion. The estimated agriculture losses
for five years 1995-2000 due to sea intrusion was estimated around Rs.265.7 million.
The losses in fisheries were estimated atRs.3.15 million/year. The study revealed that
the presence of mangroves near the shoreline can controls these damages. But
unfortunately mangroves forest of value around Rs.45 million had been lost in the
period of 1995-2000.
According to the study titled “MANGROVES OF PAKISTAN” (IUCN, 2005 a), in
the area of mangroves around 100 species of fish have been recorded and 46 species
of them were fingerling or young stages while 52 in sub-adult or adult stages. The
study explained several reasons for the destruction in mangroves around the coastal
area of Pakistan. One of the reasons was the decrease of fresh water from the Indus
River and other seasonal rives. The reduced supply of fresh water reduced the delta
area from 26,000 sq.km.to 1190 sq.km. Also feeding of mangroves to camels was
recorded in this area at 120,000 kg / day.
5
Khalil (1999) studied the economic aspects of mangroves for the region of Sindh.
According to her, along the 240 km of coastline 600,000 acres of area is covered by
mangroves, in which approximately 40% of the mangroves are in entire tidal belt and
10% in theIndusdelta fan. The study showed that the mangroves ecosystem had
supported the shrimp fishery around the coastal area which has the value of US$100
million/year. Mangroves also protect Coastal area from the erosion. Khalil also
highlighted the major causes for destruction of mangroves; the reduction in water
current flow from 200 million tons to 50 million tons affected the amount of
sediments supply that directly damaged the mangroves. Also mangroves are used as
the feeding ground for the camels and cattle. The estimated consumption of
mangroves as fodder in the delta was 2,560,000 kg/year. The wood from mangroves,
used as fuel, was estimated around 11,352,240 kg/year which had approximate value
of Rs.15.2 billion/year.
Another study by IUCN (2005b) for Preliminary Compendium of Coastal and Marine
Protected Areas in Pakistan shows that currently the Indus delta region is spread over
the area of 600,000 hectares and consists of 17 major creeks, some minor creeks, mud
flats and fringing mangroves. The area of delta is very arid and the average annual
rainfall is approximately 200mm. In the past the mangrove ecosystem grew due to the
normal supply of water from the Indus River but due to the reduced water flow from
150MAF to 10MAF, the mangroves of these areaswas affected heavily. Mangroves
proved a natural habited to the fisheries and birds, due to presences of these
mangroves around 200 species of fishes had been reported in Indus delta region. .Also
52 species of water birds had been seen in the Indus delta region, most of these bird
species were using mangroves as their habitat. Unfortunately mangroves in the west
coastal area decreased from 43% to17% in 2003.
2.3 Focus Group Discussion
A number of Focused Group Discussions (FGD’s) were conducted to understand the
community relationship with mangroves. FGD’s were held both at urban and rural
areas of the three talukas. Participants were chosen in such a manner that their
participation reflected the view of all the stakeholders having relation with mangrove
forest. The group included fishermen, landlord, farmers, businessmen, shopkeepers,
local politician, social workers, teachers and officials of fisheries and forest
departments.
First, their view about the changes taken place in mangroves area over the last 50
years was recorded. Their response was similar and according to the official figures.
All the participants answered that the area of mangroves have declined substantially
over the last 50 year. According to the participants the reasons behind the reduction
are: reduced supply of sweet water and sediments, over cutting of mangroves for sale
of timber, fuel wood and poles for housing. Participants also criticized decision of the
government about restriction on the Indus water flows at Kotri barrage in 1960 and
held that responsible for the reduction in mangroves cover. Some stakeholders also
highlighted that the cutting of the mangroves is due to the unawareness among the
community about its importance. Another reason came under discussion was owners
of camels were using mangroves for camel grazing.
6
Second, the participants were asked to rank the external factors for the destruction of
mangroves in the area. The participant ranks these in the following order of
significance.
1. Sea cyclone
2. Sea level rise
3. Lack of sweet water
4. Illegal fishing nets
5. Commercial cutting of mangroves forest
Third, its importance was discussed to get an overview of the participant’s knowledge
about mangroves. Participants argued that mangroves are very necessary for the
coastal development because these protect community from sea cyclone.
Fourth, the discussion was also done on the effort put forward by different
organization for the development of mangroves. According to the participants a
number of efforts were made by the different organization to reduce the losses in the
area of mangroves. The major work is done by the United Development & Welfare
Organization. They declared area under mangrove as no cutting zone due to which
about 300 hectares of the mangroves is now safe from cutting. Participants also
pointed out that IUCN and the Forest Department are working on the new plantation
of the mangroves that will increase the area of mangroves. Further to
this,theparticipants stressed that the appointment of forest guards will improves the
implement of the No Cutting Zone Law. According to the group, the major
organizations that worked for the preservation of mangroves includes; WWF, IUCN,
NRCP, Aga Khan Foundation, Forest Department and other Local NGO`s. these
organizations are creating awareness in the local community about importance of
mangroves.
Fifth, the group also shed light on the benefits that they are obtaining from
mangroves. They drew attention towards many benefits such as mangroves providing
nursery to the fishes, and serving as habitat for the breeding of other species as well. It
also protects the coastal area from the destruction of sea cyclone - by acting as the fist
line of defense against the sea cyclone. Some participant also pointed out that the
community is using wood from mangrove forest as fuel. The wood from mangroves
produced less smoke as compared to other wood. The community is also using wood
(poles) for building houses. According to the participants the mangroves serve as a
breading place for fish, crabs and prawns that provide monetary benefits to the
fisherman. Small amount of honey and marori production were also been reported by
the participant. Few members also reported that they are hunting a snake named
“Lundi” from the mangroves, used in medicine by the community.
Finally the team asked the participant If the community is willingness to participate in
the improvement or plantation of mangroves? The members responded that the
community can spend 1 - 4 days in a month working for the improvement and
plantation as voluntary labour. According to the members, the community can provide
limited financial contribution for the development of mangroves but the people of the
community are generally not financially strong enough. They emphasized that if
government or NGO’s offer monetary compensation as incentive for mangroves
protection then a large number of community members will participate in mangroves
development.
7
3. BACKGROUND OF THE INDUS DELTA
The Indus delta is a triangular fan-shaped delta and covers around 3 million hectares
area of Sindh.PresentlyIndusdelta occupies an area ofaround 600,000 hectares.The
area compromises 17 major creeks and many minor creeks,mud flats and fringing
mangroves (MeynellandQureshi 1993). The mangrove ecosystem of
theIndusdeltaisthelargest area in the arid climate in theworld. According to Memon
(2005) mangrove of delta covers 263,000 hectares area and it is the sixth largest in the
world.
Memon (2005) highlighted a number of benefits from these mangroves forests to the
community. According to Memon, mangroves provide a transition from the fresh
inland waters to the salty Arabian Sea and actsashabitat for numerous species like
fish, shrimp, lobsters and crabs. It also acts as windbreaker and prevents storms from
reaching inland and prevents any coastal land erosion.
However, Memon (2005) has reported that the mangroves found in Indus delta are not
so diverse. The area is mainly composed of Avicennia marina, a species that is highly
resistant to salinity and is capable of surviving in the region's extreme conditions.
Other species found in Pakistan with their geographical spread isreflected in the
following table:
Table – 3.1
List and Distribution of Mangrove Species in Pakistan
Species Distribution
RHIZOPHORACEAE
Bruguieragymnorhiza (L) Lamk.
Karachi and Indus delta (Hassan) Estuary of
Indus (Murray); no specimen in Kew,
Edinburgh and Pakistan.
Ceriopstagal (Perr.) C.B. Robin Karachi and Coast of Sindh (Stocks) Mouth of
Indus and “Salt Water Creek” (Murray)
Ceriopsdecandra (G.) Ding Hou Sindh tidal zone; existence considered
doubtful
RhizophoramucronataLamk. Tidal marshes at the mouth of Indus:
MianiHor, Las Bella (T&S)
MYRSINACEAE
Aegicerascorniculatum (L.) Blco. Mangrove swamps at mouth of the Indus
(Stocks Ritchie) Karachi (Jafri), KalmatHor
AVICENNIACEAE
Avicennia marina (Forstk.) Vierh. Tidal mangrove swamps; Sands Pit (Stem)
China Creek, etc. (Jafri), KalmatHor
SONNERA TIACEAE
SonneratiaCaseolaris (L.) Engler Mouth of Indus and Tidal Zone (Common,
fide Murray); Indus delta no specimen seen.
Source: Coastal Environmental Management Plan for Pakistan-UN-ESCAP, 1989.
8
Keti Bunder
Keti Bunder is located at a distance of about 200 km south east of Karachi in Thatta
district of Sindh province. It is a taluka (Tehsil) of Thatta district and consists of a
total of 42 dehs (villages) that spread over a total area of 60,969 hectares
(WWF-2008). According to WWF (2004), the sea has engulfed 28 dehs and the total
affected area in Keti Bunder was around 46,137 hectares. The communities are
mainly depended on agriculture and fishing for livelihood. Livestock farming is also
common in Keti Bunder, communities reported raising cattle, buffaloes and camels.
According to Hoekstra et al.(1997) there were about 5000 camels in mangrove areas.
Earlier Qureshi (1985) had reported somewhat higher figure of 16,000 camels in the
entire deltaic region.
According to WWF (2008) report on ketibunder, area under mangrove is around
7,241 ha out of which 1,578 ha area(22% of total area) falls under dense mangroves
forest . The locals community uses mangrove trees for fodder, as fuel wood, camel
browsing and for making of huts. As Mangroves are also the breeding ground for
variety of fish shrimps, crabs and other invertebrates as well, the livelihood of the
people of ketibunder is directly depended on the mangrove. Over all dominant
sources of livelihood includes fishing (about 90%), agriculture and livestock rearing
(about 8%) and services in various sectors (about 2%). The area of mangroves has
declined over the period of 1932 -2005,see Below tables for further tables.
Table – 3.2(a)
Mangroves Density in Keti Bunder (Hectares)
Mangroves Density Classes Mangroves
Area % of Total
Mangroves Area
Dense 1,578 22%
Medium 1,338 18%
Sparse 2,886 40%
Very Sparse 1,439 20%
Source: WWF-2008, based on GIS images.
Table – 3.2(b)
Historical Pattern of Area under Mangroves in Pakistan (Hectares)
Years Mangroves Area
1932 604,870
1986 440,000
1992 160,000
2005 86,000
Sources: 1. Coastal EnvironmentalManagement plan for Pakistan UNESCAP,1996.
2. Mangroves of Pakistan- and Management, IUCN,Pakistan, 2005.
Kharo Chhan
Geographical area of Kharo Chhan is about 57,459 ha. The area can be sub-divided
into two main areas i.e. inland areas and mudflat areas. According to the 1998 census
9
the population of taluka Kharo Chhan and adjacent creeks was about 30,500. The
major sources of livelihood were fishing, agriculture and livestock.
In 2011, WWF conducted a GIS based study to compare the area of Kharo Chhan
before and after flood. According to the report, major dense pockets of mangrove
forests of the Indus delta are present in Kharo Chhan. The mangrove area provides
support to fishes and other species. The dense patches of mangroves mainly
compromises of Avicenna marina. However, the locals are not directly dependent on
mangroves as the forest exists at a distance of 20 kilometers. It required almost a day
to reach the area using boat. The area is very rich in terms of biodiversity. It is an
important flyoverfor migratory birds as well. During the winter season, thousands of
waterfowl stay here for feeding and breeding (see WWF-2011 for more detail).
Table – 3.3
Area Comparison of Pre and Post Flood Land Cover Classes (Hectares)
Class Name Mangroves Area
Pre-Flood Post-Flood
Closed Mangroves Canopy 3,249.32 3,25.38
Closed to open Mangroves Canopy 4,883.76 3,712.14
Source: WWF-2011, based on GIS images.
Shah Bunder
Shah Bunder is located on the Sindh costal area, its geographical area is about
3322.78 km2 which is about 19% of total geographical area of Thatta. Shah Bunder
consists of 92 Dehs.According to the population census of 1988 its population is
around 1,00,575, the recently estimations show that population has increased to
142,924. The socio economic indicators show that there are total 159 schools located
in the Shah Bunder out of which only 4 are high schools. The conditions of health
facilities are also very poor in Shah Bunder, Shah Bunder least deprived taluka of
Thatta. People of Shah Bunder have around 2000 camels,6000 buffalos, and
7000goats. The area of mangroves in Shah Bunder is not reported anywhere officially
in the absence of the official figure,we have computed the area by multiplying the
proportion of area under mangroves in Keti Bunder and KharoChhan to total
geographical area of Shah Bunder. The computer area is around 39,347 ha. The area
however is dense in the eastern part of Shah Bunder as compare to the other region of
Shah Bunder.
10
4. SOCIO-ECONOMIC PROFILE OF THE RESPONDENTS
This section of the report highlights different socio-economic profiles of 160
respondents as anoutcome of household survey in the area. These profiles, prepared
across different classifications of the respondents using the micro level data, are
important indicators of the local population which lives closest to mangrove forests
and in part depend (directly or indirectly) on the forests for their livelihood.
a) Family Size
The average family size of all sampled households was 11.27, where the minimum of
10.44 was for Shah Bunder and maximum of 13.55 for Kharo Chhan. It is interesting
to note that in Shah Bunder where the average family size was lowest (i.e. 10.44), the
average number of males (i.e. 3.46) was higher than the average number of females
(i.e. 3.21) and the associated average number of children was lowest (i.e. 3.77).
Table – 4.1
Average Family Size, Males, Females and Children (# Households)
Taluka Stats. Family Size Male Female Children
Keti Bunder
Mean 11.05 3.35 3.38 4.55
# Observations (40) (40) (40) (40)
Std. Deviation 8.24 3.15 3.36 3.49
Kharo Chhan
Mean 13.15 3.73 4.03 5.35
# Observations (40) (40) (40) (40)
Std. Deviation 6.50 2.33 2.64 3.26
Shah Bunder
Mean 10.44 3.46 3.21 3.77
# Observations (80) (80) (80) (80)
Std. Deviation 8.15 2.87 2.93 4.13
Total
Mean 11.27 3.50 3.46 4.36
# Observations (160) (160) (160) (160)
Std. Deviation 7.83 2.81 2.98 3.81
Source: Household Survey.
Conversely, in Keti Bunder and Kharo Chhan where the average number of males was
less than average number of females, the associated average number of children was
higher (i.e. 3.38 and 4.03). It shows that a larger proportion of females (in relation to
males) seem to be associated with larger number children in the family. This could be
one of the reasons for higher fertility rate.
b) Education: Respondents
The levels of education (in terms of years completed) of the respondents shows that
nearly two-third of the 160 households had no education. In terms of years completed
in school, Kharo Chhan seems to have an edge over other two talukas (Table 4.2).
11
Table – 4.2
Levels of Education of the Respondents
(# Households unless otherwise mentioned)
Education Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Illiterate
Count 26 27 49 102
% within Taluka 65.0% 67.5% 61.3% 63.8%
% of Total 16.3% 16.9% 30.6% 63.8%
1 to 5
Count 11 6 18 35
% within Taluka 27.5% 15.0% 22.5% 21.9%
% of Total 6.9% 3.8% 11.3% 21.9%
6 to 10
Count 2 4 8 14
% within Taluka 5.0% 10.0% 10.0% 8.8%
% of Total 1.3% 2.5% 5.0% 8.8%
11 to 12
Count 1 2 2 5
% within Taluka 2.5% 5.0% 2.5% 3.1%
% of Total .6% 1.3% 1.3% 3.1%
13 to 16
Count 0 1 3 4
% within Taluka .0% 2.5% 3.8% 2.5%
% of Total .0% .6% 1.9% 2.5%
Total
Count 40 40 80 160
% within Taluka 100.0% 100.0% 100.0% 100.0%
% of Total 25.0% 25.0% 50.0% 100.0%
Source: Household Survey.
c) Education: Within Family
The information on highest level of education completed within the family, the
average number of those who completed 12 years or more was 3.69 for Kharo Chhan,
3.65 for Shah Bunder and 3.4 for Keti Bunder (Table 4.3).
Table – 4.3
Higher Education Completed in the Family (# Households)
Taluka No Education Upto 5 5 to 10 10 to 12 12 & above
Keti Bunder 26 4.50 14 3.4
Kharo Chhan 27 7.54 13 3.69
Shah Bunder 49 6.77 31 3.65
Source: Household Survey.
Though the overall pattern reflects poor educational attainment in the area, Kharo
Chhan seems to have an edge over here as well in relation to other two talukas.
d) Period of Settlement
Table 4.4 shows variations in the period of settlement of the sampled households
across three talukas. The proportion of those families who have been living for over
50 years was highest in case of Kharo Chhan (i.e. 72.5).
12
Table – 4.4
Association with the Village (# Years Since Living in the Village)
Over All Frequency Percent Less than 10 Years 21 13.1 11 to 20 Years 15 9.4 21 to 30 Years 19 11.9 31 to 50 Years 25 15.6 More than 50 Years 80 50.0 Total 160 100
Keti Bunder Frequency Percent Less than 10 Years - - 11 to 20 Years 5 12.5 21 to 30 Years 9 22.5 31 to 50 Years 5 12.5 More than 50 Years 21 52.5 Total 40 100
Kharo Chhan Frequency Percent Less than 10 Years 1 2.5 11 to 20 Years 3 7.5 21 to 30 Years 2 5.0 31 to 50 Years 5 12.5 More than 50 Years 29 72.5 Total 40 100
Shah Bunder Frequency Percent Less than 10 Years 20 25.0 11 to 20 Years 7 8.8 21 to 30 Years 8 10.0 31 to 50 Years 15 18.8 More than 50 Years 30 37.5 Total 80 100
Source: Household Survey.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Keti Bander Kharo Chhan Shah Bander Overall
Less than 10 Years
21 to 30 Years
Mo
re t
han
50
Yea
rs
Mo
re t
han
50
Yea
rs
Mo
re t
han
50
Yea
rs
Mo
re t
han
50
Yea
rs
Per
cen
tag
e o
f #
Ho
use
ho
lds
13
Similarly, the proportion of those settled rather recently (i.e. less than 10 years ago)
was highest in case of Shah Bunder where 25 percent of households settled recently as
compared to zero percent in Keti Bunder and Kharo Chhan. Since Shah Bunder was
worst affected by sea cyclone in the late 1990’s as a result of which its taluka
headquarter was shifted to upland area, the shifting of settlements was more common
in Shah Bunder taluka. However, on the whole, 50 percent of sampled households
(i.e. 80 out of 160) reported to be living in the area for over 50 years.
e) Agricultural Land
The scale of devastation in thee coastal talukas as a result of continuous sea intrusion
has resulted in the loss of fertile agricultural land. Currently, agricultural land
ownership has reduced along the coastal belt of Indus delta. Only a fraction of land
holding is brought under cultivation owning to the fact that the supply of fresh water
has reduced considerably.
Table – 4.5
Agriculture Land Ownership and Cultivation (#acres)
Taluka Land Not
Owned (Household)
If Own Land Agriculture Land
Owned (acres)
Current Cultivated Area
(acres)
Keti Bunder
Mean - 10.000 .000
# Observations (39) (1) (1)
Std. Deviation - - -.
Kharo Chhan
Mean - 31.46 3.29
# Observations (28) (12) (12)
Std. Deviation - 55.24 6.13
Shah Bunder
Mean - 18.80 .850
# Observations (60) (20) (20)
Std. Deviation - 24.39 2.23
Total
Mean - 23.14 1.71
# Observations (127) (33) (33)
Std. Deviation - 38.02 4.17
Source: Household Survey.
As such, crop cultivation in coastal talukas of Keti Bunder, Kharo Chhan and Shah
Bunder is away from the coast. Table 4.5 shows that out of 160 sampled households
127 i.e. (79 percent) had no land ownership. Of those who own land, the average size
of holding in Keti Bunder was 10 acres, on which there was no cultivation. Similarly,
in Kharo Chhan and Shah Bunder, the average size of agricultural land holding was
31.46 and 18.8 acres, respectively. Out of this, only 5 to 10 percent was cultivated.
The massive devastation of fertile agricultural land also caused a virtual elimination
of historically famous red rice of the area.
f) Ownership and Value of Vehicles Owned
Table 4.6 shows the number and type of vehicles owned by the sampled household. A
total of 22 motorcycles, one jeep and 1 pick up were owned by the households. A
generally prevalent poverty in the area coupled with dilapidated conditions of roads
14
has tended to reduce the ownership of vehicles in the coastal belt. The locals use
public transport for in their daily routine work and the quality of this transport service
is very low.The economic and social backwardness of the area can be judged from the
fact that in Keti Bunder, there is not a single ambulance service available. The
patients are taken in public transport to hospitals located at 60 to 100 kilometers away
in Gharo or Thatta city.
Table – 4.6
Ownership and Value of Vehicles Owned
Ownership of Vehicles (#)
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder
Motor Cycle 4 5 13 22
Jeep - - 1 1
Car - - - -
Pick Up - 1 - 1
Value of Vehicles
(Rupees)
Motor Cycle
Jeep
Car
Pick Up
38,750
-
-
-
42,000
-
-
600,000
37,423
170,000
-
-
38,704
-
-
600,000
Source: Household Survey.
g) Ownership of Boats and Value
Since marine fisheries is the main source of livelihood and some villages are located
in islands, use and ownership of boats is common in the area. Table 4.7 reflects boat
ownership by size and value.
Table – 4.7
Ownership and Average Value and Size of Boat
(# Boats unless otherwise mentioned)
Talukas
Total Keti Bunder
Kharo Chhan Shah Bunder
Ownership of Boat (#) 30 23 36 89
Size of Boat (Feet) 23.8 25.56 26.466 25.33
Value of Boat (Rupees) 1,130,333 1,257,173.9 539,305.6 924,044.9
Source: Household Survey.
On average, the households in each taluka reported 23 to 36 boats owned with an
average size (i.e. length) around 25 feet. The average value reported ranged between
Rs.0.5 to 1.3 million rupees.
h) Ownership and Number of Livestock
The ownership of livestock was limited in the area. Only 58 households out of 160
(i.e. 36 percent) were keeping livestock. The raising of camels was reported only by
10 households with 7 from Shah Bunder (Table 4.8).
15
Table – 4.8
Ownership and Number of Livestock (#Animals)
Talukas
Total Keti Bunder
Kharo Chhan Shah
Bunder
Ownership of Livestock 6 16 36 58
Camel 30 (2) 2 (1) 46 (7) 78 (10)
Buffalos 23 (3) 17 (6) 58 (22) 98 (31)
Cows 10 (1) 14 (6) 20 (7) 44 (14)
Goats 16 (3) 27 (7) 6 (3) 49 (13)
Figures in parenthesis show # reporting households.
Source: Household Survey.
The total number of camels, buffaloes, cows and goats raised by the 58 households
were 78,98,44 and 49, respectively. The practice of keeping livestock was limited due
to the fact that some villages are located on islands and the transportation and feeding
of livestock is an uphill task for such households. The lowest stock of animals was
reported in Kharo Chhan and the highest from Shah Bunder. However, these
variabilities are largely an indicator of geographical area and population covered by
Shah Bunder (which was also taken into account while assigning weights in the
sampling framework). Nevertheless, the stock of animals kept of the households is a
reflection of the fact that these households depend on mangroves for the supply of
fodder.
i) Civic Amenities Available
Table 4.9 shows type of construction of 158 sampled households. It shows that nearly
half (48.1 percent) were living in huts, another 24.4 percent were living in semi-pacca
houses whereas 26.9 percent had pacca housing structure.
The pattern of housing construction is similar across the talukas. The proportion of
pacca housing structure in Keti Bunder was twice the proportion in Kharo Chhan and
Shah Bunder. The fact that over 48 percent of houses were established in huts
provides ample evidence of poverty levels prevailing in coastal areas.
16
Table – 4.9
# Household Connected with Various Facilities (# Households)
Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Ownership of House 40 39 79 158
1. Construction Type
- Hut 20
(50)
20
(50)
37
(46.3)
77
(48.1)
- Semi Pacca 4
(10)
12
(30)
23
(28.8)
39
(24.4)
- Pacca 16
(40)
7
(17.5)
20
(25.0)
43
(26.9)
2. Piped Drinking Water 0
(0)
0
(0)
10
(12.5)
10
(6.3)
3. Electricity 28
(70)
2
(5)
10
(12.5)
40
(25.0)
4. Gas 0
(0) 0(0)
7
(8.8)
7
(4.4)
5. # Rooms 2.63 2.74 2.29 2.48
Note: Numbers in parentheses are percentages.
Source: Household Survey.
The table also reports that 10 out of 80 households in Shah Bunder had access to
piped drinking water in their houses, whereas none of the sampled households in other
talukas had any such facility. Only in case of Keti Bunder, there is a scheme of
providing safe drinking water at a public place atits headquarter. On the whole, only
6.3 percent of households within the sampled households had access to piped drinking
water. The real situation on safe drinking water supply in Keti Bunder is that the
general water supply is provided by private tankers who bring water some 15 to 20
kilometers from a nullah located right on the main road connecting Keti Bunder with
the rest of Thatta district. The water quality is very low and the locals have no option
but to purchase low quality water at higher prices. If this is the situation in proper Keti
Bunder which has a higher proportion of urban population, the situation in other
talukas can be ascertained rather easily.
The system electricity connection was somewhat better than that of water supplies.
Nearly 70 percent of households sampled from Keti Bunder had electricity connection
whereas this proportion was low 5 percent in Kharo Chhan and 12.5 percent in Shah
Bunder.
Only 7 households of Shah Bunder had gas connections.
The situation of housing and provision of civic amenities in the coastal area of Indus
delta, so depicted, reveals extremely poor quality of life. Under this scenario, it is
expected that these coastal communities depend in part on the non-timber forest
products from mangroves to derive a number of direct and indirect benefits for their
livelihood.
17
j) Occupation
Table 4.10 provides information on primary, secondary and tertiary occupations in the
sample talukas. In Keti Bunder, 29 out of 40 (i.e. 72.5 percent) had fishing as their
primary occupation. The respective proportions were 52.5 and 43.8 percent for Kharo
Chhan and Shah Bunder, respectively. This portrays the central occupation in the
coastal area.
Table – 4.10
Occupations Primary, Secondary and Tertiary (#)
All Keti Bunder Kharo Chhan Shah Bunder
Primary Secondary Tertiary Primary Secondary Tertiary Primary Secondary Tertiary
Fishing 29
(72.5)
1
(2.5) -
21
(52.5)
3
(7.5) -
35
(43.8)
3
(3.8) -
Shop or
Business
2
(5)
3
(7.5) -
2
(5)
2
(5) -
5
(6.3) -
Labor 3
(7.5)
2
(5) -
5
(12.5) - -
25
(31.3)
1
(1.3) -
Job 5
(12.5) - -
5
(12.5
6
(15) -
7
(8.8) -
Stitching and
Tailoring
1
(2.5)
1
(2.5)
1
(2.5) -
1
(2.5) - -
3
(3.8) -
Social Worker - - - - - - 1
(1.3) - -
Fishing on
Rented Boat - - -
5
(12.5) - -
2
(2.5) - -
Wood seller - - - - 1
(2.5) -
2
(2.5)
1
(1.3) -
Farmer - - - - 2
(5) -
2
(2.5)
3
(3.8) -
Middle Man
Whole seller - - - - - -
1
(1.3) - -
Planting - 2
(25) - - - - - - -
Rent a Car - - - - - - - 1
(1.3) -
# Household 40 9 1 38 15 - 80 11 0
Total 40 40 40 38 38 38 80 80 80
Note: Figures in parentheses show column percentages.
Source: Household Survey.
Wage labourwas reported by 7.5 percent in Keti Bunder, 12.5 percent in Kharo Chhan
and 31.3 percent in Shah Bunder as primary occupation. Similarly, doing a job as
primary occupation was reported by 12.5 percent in Keti Bunder, 12.5 percent in
Kharo Chhan and 8.8 percent in Shah Bunder. It implies that 92.5 percent of sampled
households had these three occupations (namely fishing, wage labour and jobs) in
Keti Bunder. The respective proportions for Kharo Chhan and Shah Bunder were 72.5
and 83.9 percent, respectively. The exclusive dependence on fisheries reveals source
18
of livelihood for coastal community. At this, it becomes difficult to overemphasize the
direct and indirect dependence of coastal communities on mangroves.
The details on secondary occupations of these communities reveal that 9 out of 40 in
Keti Bunder, 15 out of 38 in Kharo Chhan and 11 out of 80 in Shah Bunder had a
secondary occupation as well. Putting jointly, in aggregate terms the three main
occupations account for 90 percent of households in Keti Bunder, over 95 percent in
Kharo Chhan and 90 percent in Shah Bunder. The tertiary occupations were almost
non-existence. The occupational pattern shows an inclusive dependence of coastal
communities on local natural system supported by few opportunities for wage labour
and jobs.
k) Working Force and Employment
Tables 4.11(a) to (d) provide details on average number of persons per household and
days of work per week across gender for each taluka and an overall situation covering
all sampled households.
Table – 4.11(a)
Average Workers and Days in Work in Keti Bunder (# Workers)
Taluka Keti Bunder
Male Female Children
Male Worker
Days Per Week Male
Worker
Female Worker
Days Per Week
Female Worker
Children in Work
Days per Week
Children in Work
Primary
Occupation
Mean 1.95 5.4 - - 0.25 0.72
# Observations (40) (40) (40) (40) (40) (40)
Std. Deviation 1.65 1.36 - - 0.74 1.8
Secondary
Occupation
Mean 0.28 0.75 0.15 0.2 0 0
# Observations (40) (40) (40) (40) (40) (40)
Std. Deviation 0.75 1.84 0.7 1.11 0 0
Tertiary
Occupation
Mean - - 0.03 0.08 - -
# Observations (40) (40) (40) (40) (40) (40)
Std. Deviation - - 0.158 0.47 - -
Source: Household Survey.
In Keti Bunder, employment of males in primary and secondary work accounted for
1.95 and 0.28 workers per households, respectively. The respective numbers of hours
per week for males were 5.4 and 0.75 days. There was primary occupation reported
for females. The number of children, on average, was 0.25 and they worked for 0.72
days per week in the primary sector. The secondary occupation was taken, on average,
by 0.28 males and 0.15 females per household. There was no child work reported in
secondary occupation (Table 4.11(a)). There are limited tertiary occupations reported
for females in the area.
19
Table – 4.11(b)
Average Workers and Days in Work in Kharo Chhan (# Workers)
Taluka Kharo Chhan
Male Female Children
Male Worker
Days Per Week Male
Worker
Female Worker
Days Per Week
Female Worker
Children in Work
Days per Week
Children in Work
Primary
Occupation
Mean 2.55 5.05 - - 0.13 0.29
# Observations (38) (38) (38) (38) (38) (38)
Std. Deviation 1.8 1.66 - - 0.67 1.29
Secondary
Occupation
Mean 0.53 1.26 0.03 0.03 0.13 0.42
# Observations (38) (38) (38) (38) (38) (38)
Std. Deviation 1.37 2.37 0.16 0.16 0.53 1.5
Tertiary
Occupation
Mean - - - - - -
# Observations (38) (38) (38) (38) (38) (38)
Std. Deviation - - - - - -
Source: Household Survey.
In Kharo Chhan, employment of males in primary and secondary work accounted for
2.55 and 0.53 persons per household. There was no female work reported. In case of
children, on average, 0.13 children per households worked for 0.29 days per week.
For secondary occupations, 0.53 males, 0.03 females and 0.13 children remained
associated who, respectively, devoted 1.26, 0.03 and 0.42 days per week
(Table 4.11(b)). There was no reporting of any tertiary occupation in the area.
Table – 4.11(c)
Average Workers and Days in Work in Shah Bunder (# Workers)
Taluka Shah Bunder
Male Female Children
Male Worker
Days Per Week Male
Worker
Female Worker
Days Per Week
Female Worker
Children in Work
Days per Week
Children in Work
Primary
Occupation
Mean 2.28 5.86 - - 0.01 0.05
# Observations (80) (80) (80) (80) (80) (80)
Std. Deviation 1.82 1.31 - - 0.11 0.45
Secondary
Occupation
Mean 0.28 0.55 0.03 0.14 0.01 0.08
# Observations (80) (80) (80) (80) (80) (80)
Std. Deviation 0.94 1.6 0.16 0.87 0.11 0.67
Tertiary
Occupation
Mean - - - - - -
# Observations (80) (80) (80) (80) (80) (80)
Std. Deviation - - - - - -
Source: Household Survey.
In Shah Bunder, the number of males and children involved in primary occupations
were, respectively, 2.28 and 0.01. No female participation was reported in primary
occupation. These persons devoted 5.86 days and 0.05 days per week in carrying out
their work in primary occupation. In the secondary occupation, the males participation
was on average, 0.28 persons per household, 0.03 persons for females and 0.01 for
children.
20
Table – 4.11(d)
Average Workers and Days in Work in All talukas (# Workers)
All Taluka
Male Female Children
Male Worker
Days Per Week Male
Worker
Female Worker
Days Per Week
Female Worker
Children in Work
Days per Week
Children in Work
Primary
Occupation
Mean 2.26 5.55 - - 0.1 0.28
# Observations (158) (158) (158) (158) (158) (158)
Std. Deviation 1.77 1.44 0 0 0.51 1.17
Secondary
Occupation
Mean 0.34 0.77 0.06 0.13 0.04 0.14
# Observations (158) (158) (158) (158) (158) (158)
Std. Deviation 1.02 1.88 0.38 0.83 0.27 0.89
Tertiary
Occupation
Mean - .- 0.01 0.02 - -
# Observations (158) (158) (158) (158) (158) (158)
Std. Deviation - - 0.08 0.24 - -
Source: Household Survey.
At all taluka level, the situation has been summarized in Table 4.11(d). In case of
males, 2.26 and 0.34 persons i.e. 2.60 persons per household were employed.
Similarly, in case of females it shows a total of 0.07 females per household employed
in any occupation. The child work jointly shows an average of 0.14 children per
household involved in any occupation.
In terms of days per week of work, it reported 6.13 days, for males, 0.15 days for
females and 0.42 days of children, across all occupations.
The levels of employment across gender reported in Table 4.11(d) when compared
with average number of persons in the household reported in Table 4.1 (discussed
earlier) shows that males employment level was 74 percent ( i.e. 2.60 in relation to
3.50), females employment level of 20 percent (i.e. 0.7 in relation to 3.46) and
children was 4 percent (i.e. 0.14 in relation to 4.36).
Keeping in consideration the old age persons in families, the employment of working
force of males of 74 percent seems close to full employment level. However, female
employment of 20 percent seems underutilization of available female labour force.
The child work of 4 percent, though relatively low, creates concern.
l) Income Levels
Keeping in view all sources of direct incomes (i.e. on-site and off-sites) of all males,
females and children as reported during household survey, total monthly income
levels were computed for each taluka. Table 4.12(a) shows wide variations across
talukas.
21
Table – 4.12(a)
Average Household Income by Taluka (Rs./Month)
Taluka Mean # Observations Std. Deviation
Keti Bunder 64,340 40 121,129
Kharo Chhan 36,621 38 68,329
Shah Bunder 15,743 80 13,269
Total 33,067 158 72,378
Source: Household Survey.
The levels, though presented for each taluka on the basis of monthly averages, show
wide variations in Keti Bunder and Kharo Chhan talukas, reported through their
respective levels of standard deviation.
Only in case of Shah Bunder the average level does not show significant variation. If
Shah Bunder’s average income level is taken as base, it implies that at Keti Bunder,
the direct incomes were over 4 times and that of Kharo Chhan there were more than
twice in relation to Shah Bunder.
Table – 4.12(b)
Number of Household across Income Categories (# Households)
Income Category Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
0 thru 5000 4 2 14 20
10.00% 5.30% 17.50% 12.70%
5001 thru 10000 6 14 20 40
15.00% 36.80% 25.00% 25.30%
10001 thru 20000 15 11 26 52
37.50% 28.90% 32.50% 32.90%
20001 thru 40000 3 5 17 25
7.50% 13.20% 21.30% 15.80%
40001 thru hi 12 6 3 21
30.00% 15.80% 3.80% 13.30%
Total 40 38 80 158
100.00% 100.00% 100.00% 100.00% Note: Percentages show column percentages.
Source: Household Survey.
22
The income level variability discussed above was further analysed across different
income categories which is presented by Table 12(b). It further verifies that Shah
Bunder area consists of larger proportion of low income categories in relation to other
two talukas. For example, upto an average monthly income of Rs.10,000, Keti Bunder
has 25 percent of households, Kharo Chhan 42.1 percent and Shah Bunder 42.5
percent.
Similarly in higher income category of Rs.40,000 and above per month, Keti Bunder
has 30 percent of its households, Kharo Chhan 15.8 percent and Shah Bunder only
3.80 percent.
A common view of the area reflects the fact that Keti Bunder has retained its
historical location as well as has acted as a center for various developmental activities
despite facing a number of threats in the form of natural as well as man made
disasters. In contrast, Shah Bunder could not sustain the devastation of sea cyclone of
mid 1990’s and as a result its taluka headquarter was shifted to another location in the
upstream area, its population was scattered and as such currently the location of Shah
Bunder’s proper settlement is lost to antiquity. As a consequence, Shah Bunder has
yet not reversed its position undermining its fisheries catch and marketing and other
economic development prospects.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Keti Bander Kharo Chhan Shah Bander Total
0 thru 5000 0 thru 5000
Per
cen
tag
e o
f #
Ho
use
ho
lds
23
Table – 4.12(c)
Average Income Level under Different Scenarios (Rs./Household/Month)
Taluka If Fishing is
Primary Occupation
If Fishing is Secondary Occupation
If Non-Fishing is Primary
Occupation
If Non-Fishing is Secondary Occupation
Keti Bunder
Mean 62,531 7,000 66,272 145,525
# Observations (29) (1) (11) (8)
Std. Deviation 92,188 1,835 182,238 213,389
Kharo Chhan
Mean 52,938 2,700 13,752 21,150
# Observations (21) (3) (17) (12)
Std. Deviation 86,785 4,000 14,207 29,944
Shah Bunder
Mean 20,474 6,000 11,328 27,377
# Observations (35) (3) (45) (9)
Std. Deviation 16,332 3,191 7,719 24,213
Total
Mean 42,843 4,728 20,172 57,393
# Observations (85) (7) (73) (29)
Std. Deviation 71,427 71,254.2 122,373
Source: Household Survey.
The levels of incomes generated from fishing and non-fishing sources have been
highlighted by Table 4.12(c). It shows that income levels from fishing as primary
occupation in all talukas in terms of the levels and spread. However, fisheries as a
source of income was highest in Keti Bunder where 29 out of 40 households (72.5
percent) had it as primary occupation. In case of Kharo Chhan it was 52.5 percent and
in Shah Bunder it was 43.8 percent, of the sampled households. The highest
participation was in fisheries activities all across. The occurrence of non-fisheries was
highest in Shah Bunder.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
If Fishing isPrimary
Occupation
If Fishing isSecondaryOccupation
If Non-Fishing If Non-Fishing isSecondaryOccupation
Per
cen
tag
e o
f #
Ho
use
ho
lds
24
In relative terms, a somewhat higher attainment of education in Shah Bunder
(discussed earlier in sub-sections b & c) on educational attainments, and a higher
proportion of wage labour (reference Table 4.10) could have created the basis for
higher non-fisheries activities as secondary occupations. In any case fisheries is the
highest and more reliable source of income for the majority of coastal population.
m) Community’s Linkage with Mangroves
Over 90 percent of the respondents reported visiting mangroves either exclusively to
collect forest products like fuel wood, fodder, catching fish crabs, shrimps, honey,
herbs, poles for use in house construction, animal browsing, or to take rest and
recreation while going towards open sea for fishing.
Table – 4.13
Community’s Linkage with Mangrove (# Households)
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder
No. of Households
Visiting Mangroves
38
(95)
35
(87.5)
72
(90)
145
(90.6)
# Visits / Month 11.38 4,42 4.19 6.08
Fuel Cost* 30,879
(N=14)
16,000
(N=4)
42,857
(N=14)
34,259
(N=32)
Permit Cost* 114
(N=14)
50
(N=4)
454
(N=14)
255
(N=32)
Depreciation Cost* 4,779
(N=14)
3,075
(N=4)
3,964
(N=14)
4,209
(N=32)
Food Cost* 20,664
(N=14)
8,750
(N=4)
16,929
(N=14)
17,541
(N=32)
Other Cost* 218
(N=14)
0
(N= 4)
500
(N=14)
314
(N=32)
Note: 1. Numbers in parentheses are percentages otherwise indicated.
2. * if using to visit mangrove or using it for both, fishing & Visiting Mangroves.
Source: Household Survey.
Table 4.13 highlights the cost structure of 14 respondents who regularly visit
mangroves (i.e. 6.08 visits per month) to collect non-timber forest products. It should
also be noted that only 89 boats ownership was reported by 160 sampled households
(Table 4.7). Even if we assume that one household doesn’t own more than one boat, if
implies that over 44 percent of sampled households do not own boat. It does not mean
that non-boat owners do not visit mangrove. They may do so as part of the team (or as
wage labour). It also does not mean that all the boat owners visit mangrove. Some (or
a majority) may go directly into open sea.
Keeping all such scenarios into consideration, it is possible that a majority may visit
mangroves (either as part of primary or secondary occupation) but some of them may
not own boat and only visit as part of the team. In this context, the detailed
information on costs incurred could only be reported by the boat owner (or any one
who keeps account of such expenses). In the light of above, only 14 respondents gave
25
details on costs incurred whereas a much larger number of persons may have visited
mangroves.
The highest number of visits to mangroves was reported by respondents of Keti
Bunder i.e. 11.38 visits per month. It can thus be argued that fishermen (or coastal
population) of Keti Bunder visits mangroves more frequently than those visiting from
other talukas.
It could also be argued that for the marketing of non-timber forest products Keti
Bunder still acts as a major centre. As a result, most of the visitors may go rather
frequently to mangroves. In either case, it looks apparent that the local communities
depend on mangroves for a variety of reasons.
n) Community’s Perceptions towards Mangroves
In addition to direct questions on the quantitative aspects of valuation of mangroves,
the respondents were also asked to reveal their perceptions towards mangroves
through a set of questions.
Table – 4.14(a)
Change in Mangroves Area in Last 50 Years (# Households)
Status Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
No Change - 2
(5.1)
9
(11.4)
11
(7.0)
Increase or Improvement 2
(5.0) -
4
(5.1)
6
(3.8)
Decrease or Reduction or
destroyed
38
(95.0)
37
(94.9)
66
(83.5)
141
(89.2)
Total 40
(100.0)
39
(100.0)
79
(100.0)
158
(100.0)
Note: Numbers in parentheses are column percentages.
Source: Household Survey.
When inquired about changes in mangroves cover during the last 50 years or so, a
vast majority (nearly 90 percent) reported that the cover has reduced or destroyed
during this period (Table 4.14(a)).
26
Table – 4.14(b)
Causes of Change in Mangroves Area in Last 50 Years (# Households)
Causes Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Cutting 29
(72.5)
2
(5.1)
8
(10.1)
39
(24.7)
Camel Grazing 3
(7.5) - -
3
(1.9)
Lack of sweet water 2
(5.0)
20
(51.3)
7
(8.9)
29
(18.4)
Sea Intrusion and Cyclone 3
(7.5)
13
(33.3)
50
(63.3)
66
(41.8)
Improper Care 1
(2.5)
2
(5.1)
1
(1.3)
4
(2.5)
Total 38
(95.0)
37
(94.9)
66
(83.5)
141
(89.2)
No Change 2
(5.0)
2
(5.1)
13
(16.5)
17
(10.8)
Note: Numbers in parentheses are column percentages.
Source: Household Survey.
The respondents indicated different causes for this destruction of mangroves. A vast
majority (41.8 percent) regarded sea intrusion and cyclone as the main cause of
destruction. Out of 66 respondents, 50 were from Shah Bunder. Since the mid 1990’s
sea cyclone created higher level damages in Shah Bunder, it was not surprising that
this cause was considered as the major reason for destruction. Nearly 24.7 percent
(i.e. 39 respondents) regarded cutting of mangrove in the past as the second major
cause of mangrove destruction. Here, 29 respondents out of 39 were from Keti
Bunder. Another major cause was attributed to lack of sweet water in the deltaic
region. Here, the majority came from Kharo Chhan where 20 out of 29 respondents
were located. The other factor like camel grazing or improper care of mangroves was
reported by few (Table 4.14(b)).
Table – 4.15(a)
Changein Mangroves Area in Last 10 Years (# Households)
Status Talukas
Total Keti Bunder
Kharo Chhan
Shah Bunder
No Change - 1
(2.6) 6
(7.6) 7
(4.4)
Increase or Improvement 40
(100.0) 37
(94.9) 71
(89.9) 148
(93.7) Decrease or Reduction or destroyed
- 1
(2.6) 2
(2.5) 3
(1.9)
Total 40
(100.0) 39
(100.0) 79
(100.0) 158
(100.0)
Note: Numbers in parentheses are column percentages.
Source: Household Survey.
27
The respondents were also asked as to what happened to mangroves during the last 10
years i.e. post-sea cyclone period. A predominantly high proportion of respondents
i.e. 93.7 percent regarded the mangroves to improve during the last ten years. At this,
all three talukas unanimously agreed that a reversal has started towards mangroves
development (Table 4.15(a)).
Table – 4.15(b)
Suggested Methods of Improvement in Mangroves Area (# Households)
Causes Talukas
Total Keti Bunder
Kharo Chhan
Shah Bunder
New Plantation 34
(85.0)
27
(69.2)
44
(55.7)
105
(66.5)
Ban on Cutting - - 1
(1.3)
1
(.6)
Ban on Camel Grazing 3
(7.5)
1
(2.6) -
4
(2.5)
Proper Care 3
(7.5)
3
(7.7)
14
(17.7)
20
(12.7)
Naturally - 6
(15.4)
12
(15.2)
18
(11.4)
Total 40
(100.0)
37
(94.9)
71
(89.9)
148
(93.7)
No Change - 2
(5.1)
8
(10.1)
10
(6.3)
Note: Numbers in parentheses are column percentages.
Source: Household Survey.
When inquired about the reasons for improvements in mangrove, nearly two thirds
(i.e. 105 respondents) regarded new plantation and another 12.7 percent regarded
proper care of mangroves as the main factors behind the improvements in mangroves
cover. Only 10 respondents argued that no change took place in the status of
mangrove cover (Table 4.15(b)).
Based on the responses of sampled households towards different socio-economic
aspects, it becomes clearer that local community heavily depends on fisheries as their
exclusive source of livelihood. The incomes are largely generated from fishing
whereas the non-fishing occupations generate over one third of their incomes.
28
5. ECONOMIC VALUATION OF MANGROVES - METHODOLOGY
In order to evaluate economic value of the natural resources economists have long
preferred estimation of total economic value. The total economic value of mangrove
consists of its use value and non-use value. Use values are further classified into
direct and indirect uses. Non use value on the other hand is based on the satisfaction
consumers derive from knowing that mangroves will exist (option value). A consumer
may or may not necessarily use them. Another possible motive of non-use value is the
desire to preserve mangroves for future generations (bequest value).
Direct benefits are referred here to all the benefits derived from use of the mangrove.
In order to appropriately measure the benefits market prices werebe used. Direct
benefits of mangroves; include wood used for fuel, poles, herbs, shrimps and fish
species. The indirect benefits are hard to estimate as market prices are not available
for these benefits. Indirect benefits derived from mangroves include shoreline
protection, carbon sequestration, habitat for wild animals. These benefits are
sometime difficult to measure. In literature the estimation of indirect benefits such as
shore line protection from tsunami is based on damage costs avoided from the
destruction of economically valuable assets. However, in most of the cases it is based
on assumptions only. For the estimation purposesinformation on the cost of property
destroyed, livelihood loss, injuries and deaths were usually obtained from the site with
mangrove forest and from a control site (not covered by forest). The difference value
of the two costs was then used in literature as the economic benefits of the mangroves.
Under the non use value, option value represents the direct and indirect use of
mangroves in future while the bequest value indicates as to how much individuals
value the use and non use values for their future generation. Option values are often
used as the estimated value that people are willing to pay (WTP) in order to preserve
the mangrove for the use of future generation. This is based on the knowledge that
individual have about the preservation.
5.1 Estimating the Willingness to Pay
There is an on-going debate on how to evaluate the economic benefits of mangroves.
All these studies differ first, because of the range of products obtained from forest
varies; secondly, the types of mangrove management alternatives considered differ for
each study; thirdly, the assumptions regarding ecological linkages of mangroves and
other ecosystems are inconsistent.
There are several methods that researchers have used to evaluate the economic benefit
of the mangroves. Willingness to Pay (WTP) is one of the methods. WTP is often
used to figure out the amount of money local community is willing to spend to restore
or improve the mangrove forest culture.
Researchers have identified two methods to estimate WTP. It can be determined
indirectly by estimating the travel costs or through directly asking how much they are
willing to pay. Travel cost method estimates what people actually pay to protect the
mangrove forest while the direct method differs from traveling cost as it measures
what individuals claim to pay (Clawson et al., 1966; Bockstael et al., 1996 and Carr
et al., 2003). Their willingness to pay is based on the benefits availed form the
29
mangroves. The limitation of this method is that not all the services obtained from the
forest are commercially marketed goods. In the absence of any other method the
second method was used. For this, all the direct and indirect benefits availed from the
forest were quantified.
Second method as stated above determines WTP by asking people how much they
would be willing to pay to restore or maintain mangrove culture (Follain et al., 1985;
Malpezzi, 2008). Socio economic and demographic variables as well as economic
benefits availed from the forest were used to predict the WTP.
The willingness to pay (WTP) was considered as dependent variable:
WTP = B0 - B1(Rs. X1) + B2(X2)+B3 (X3) +B4 (X4) …
B’s are the coefficients to be estimated, Rs.X1 is the amount household was willing to
pay, X2was household income, X3 was highest education completed in years while X4
wasrespondent's family size. The formula to calculate expected WTP was based on
given Haneman (1989) formula:
Mean WTP = (1/B1) * ln[1+𝑒𝛽0+∑𝛽𝑖+𝑋𝑖]
Where, B1was the estimated coefficient of the amount household were willing to pay
and B0was the constant, Bi were the coefficients of independent variables δi were the
mean of independent variables (Hanemann, 1989).
Normally the WTP data is one where the observations at or below zero are censored.
This is because individual may response as: why to pay? What to pay? These forest
are free government may not used the amount collected properly etc. It is important to
note that not all those who gave reasons for not willing to pay are against to protect
forest. They may like to preserve the forest as well. One way of dealing these
responses is to consider the response as invalid and discard the observation. But
discarding these responses may lead to selection bias problem as the sample will not
remain random. The estimated parameters after discarding these cases will become
biased/ inconsistent. In order to avoid this problem Tobit model approach was
followed. Tobit model is an extension of the probit model and is mainly applied when
we have censored data. The standard Tobit model is based on the latent variable
approach. Finally, Emezrton and Kekulandala (2003) have listed a number of techniques to
evaluate the cost and benefits associated with the Mangroves. All the values are
measured in terms of their effects on human life, usually in monetary terms.
Moreover, the techniques listed by Emerton and Kekulandala (2003)are mostly survey
based and allow researchers to evaluate the cost and benefits in local values. This also
helps in assessing non-market as well as market value of the mangroves.
30
Chart – 5.1
Assessment of Total Economic Value of Mangroves
Source: Breidert, Hahsler and Reutterer (2006).
5.2 Economic Valuation of Mangroves - Empirical Valuation
5.2.1 Estimating Direct Values
a) Forest Product – Wood Fuel
Khalil (1999) estimated that the daily household use of wood obtained from
mangroves in the Indus delta, was around 4.5 kg/household/day. The average
price estimated was around Rs.1.45 per kg. The overall value of fuel wood
estimated by Khalil was around Rs.22.5 million per year (approximately US$
385,000/yr). While, Keerio and Bhatti (1999) indicated that wood obtained
from Avicennia marina has lower caloric value hence not desirable as fuel
wood. But it is still used by the local people extensively as fuel wood.
However its market outside the coastal area is very limited almost
negligible.According to Keerio and Bhatti (1999) each household is
consuming 173 kg of wood per month. The rate per kg varies from Rs.1 to 1.5
giving an average value of around Rs.173 to 259.5 per month (Annexure
Tables 5.1 & 5.2).
Table – 5.1
Economic Valuation of Fuel Wood (Marketed) (Rs.)
Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Total
425a 410 681 549
(1059)b (732) (1609) (1308)
(40)c (40) (80) (160)
Note: a,
b and
c are Value, Standard Deviation and # Observations, respectively.
Source: Household Survey.
31
Table – 5.2
Economic Valuation of Fuel Wood Non-Marketed (Domestic Use)
(Rs.)
Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Total
1160 490 765 795
(1444) (1038) (1665) (1487)
(40) (40) (80) (160)
Source: Household Survey.
0
200
400
600
800
1000
Subsistence Low Middle High
Eco
no
mic
Valu
e (
Rs.)
Income Levels
Figure - 5.1
Economic Valuation of Fuel Wood (Marketed) across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
0
500
1000
1500
2000
Subsistence Low Middle High
Eco
no
mic
Valu
e (
Rs.)
Income Levels
Figure - 5.2
Economic Valuation of Fuel Wood Non-Marketed (Domestic Use) across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
32
The data obtained through primary survey for this study shows that wood
obtained from the mangroves forest is not only used by households for
domestic purpose (non marketed) but also for commercial purpose as well.
Sale of fuel wood is also generating livelihood for the households (marketed).
Average value of the wood used as fuel domestically was worth Rs.795 per
month while the fuel wood marketed was worth Rs.549 per month (Tables 5.1
& 5.2). The overall value of fuel wood obtained from the mangrove forest was
therefore around Rs.1,344 per month. The economic value is highest for Keti
Bunder (Rs.1585 per month) while the value is lowest for KharoChhan
(Rs.900 per month). The lowest value for Kharo Chhan is because of the
distance (approximately 20 km) between the community and the forest area
(Detailed information across households of different income categories is
provided in Appendix Table).
b) Forest Product – Poles and Wood for Housing
Although literature has identified that the wood form the mangrove forest is
used for the building houses or building poles as well but our data shows that
in Keti Bunder, the community is not dependent on the wood for building
houses neither the community is using mangrove forest for building poles. The
overall economic value of wood used for building houses or poles is estimated
around Rs.111 per month only. The value is higher for Kharo Chhan area
(Rs.300 per month) while for Shah Bunder the economic value is around 150
per month only (Table 5.3).
Table – 5.3
Economic Valuation of Wood for Pole and House Construction (Rs.)
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder Pole
Marketed Wood for Housing
Pole Marketed
Wood for Housing
Pole Marketed
Wood for Housing
Pole Marketed
Wood for Housing
Total
- - 150 150 148 50 111 62
- - (662) (802) (1125) (447) (861) (510)
(40) (40) (40) (40) (80) (80) (160) (160)
Source: Household Survey.
0
100
200
300
400
500
Subsistence Low Middle High
Eco
no
mic
Valu
e (
Rs.)
Income Levels
Figure - 5.3(a)
Economic Valuation of Wood for Pole across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
33
c) Forest Product – Animal Browsing (Camel and Goat)
Khalil (1999) suggested that the mangrove leaves (including Avicennia
marina) are very nutritious, and support 16,000 camels and 11,000 cattle.
Based on the data from a household survey,Khalil estimated that the Indus
delta yielded 2 million kg of fodder per year that was worth Rs 2.56 million
per year.Her valuation was based on a price of Rs 1.25 per kg of mangrove
fodder.Keerio and Bhatti (1999) estimated that mangroves are populated with
the cattles beyond their capacity to produce fodder to feed. According to
Keerio and Bhatti (1999) there were 6000 camels, 3200 buffaloes and about
8000 goats, sheep and cows dependent on mangroves.
Table – 5.4
Cattle Population in Mangrove Forest Area (#)
Cattles
# Camels # Buffaloes
Total 6,000 3,200
Source: IUCN.
0
100
200
300
400
500
Subsistence Low Middle High
Eco
no
mic
Valu
e (
Rs.)
Income Levels
Figure - 5.3(b)
Economic Valuation of House Construction across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
34
Table – 5.5.1
Number of Goats and Camels (#)
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder
# Goats #
Camels # Goats
# Camels
# Goats #
Camels # Goats
# Camels
Total 16 30 27 2 6 46 49 78
Source: Household Survey.
0
500
1000
1500
2000
Keti Bunder Kharo Chhan Central ShahBunder
East ShahBunder
Ec
on
om
ic V
alu
e (
Rs
.)
Talukas
Figure - 5.4
Camel Population in Mangrove Forest Area
# Camels # Buffaloes
0
5
10
15
20
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.5.1(a)
Number of Goats across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
35
Table – 5.5.2
Numbers of Buffaloes and Cows (# Animals)
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder #
Buffalos # Cows
# Buffalos
# Cows #
Buffalos # Cows
# Buffalos
# Cows
Total 23 10 17 14 58 20 98 44
Source: Household Survey.
0
10
20
30
40
50
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.5.1(b)
Number of Camels across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
0
5
10
15
20
25
30
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.5.2(a)
Number of Buffaloes across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
36
Although Table 5.4 extracted from Shah (1999) shows high population of
camels and buffaloes but our sample survey show very low presence of
animals in the three talukas. Overall 269 animals were reported in the sample
survey (49 goats + 78 camel + 98 buffaloes + 44 cows by 160 households
surveyed). The number is higher for Shah Bunder while lowest for Kharo
Chhan. According to Khalil (1999) on average, fodder consumption per
animal unit was 3.82 kg/day, of which 1.22 kg were mangrove leaves. Hence
overall mangroves represent some 32% of domestic animal feed.
In order to estimate the costs of fodder obtained from mangrove forest,the
estimated total economic requirement were based on the Khalil data (3.82 kg
per day per animal) around 269 animals * 3.82 kg/day = 1,027.6 kg/day/animal.
Second, as only the 32% of fodder is based on mangrove leaves, the economic
value of fodder obtained from mangrove was estimated
[(1027.6 * 32)/100=328.8 kg/day]. Finally we converted the daily value on
monthly requirements(after assuming the price per Kg equals Re.1) as
Rs.9,864/month.
d) Forest Product – Herbs and Medicines
Ruitenbeek (1992) for Indonesia estimated an annual benefit for medicinal
plants of US$ 15/ha for mangroves.The value is based on a general estimate of
the biodiversity value in forests that can be captured. For Pakistan none of the
studies have confirmed the use of Mangrove as herbs or medicines. It was
assumed that the economic benefits of the mangroves do not include
medicines or herbs. But contradictory to the assumptions,it was observed
during visits to Keti Bunder that a group of people was picking Maroore
(a herb found in the stem of mangrove trees). According to the local people
Maroore is used as medicine and they earn around Rs.50 per kg.
0
2
4
6
8
10
12
14
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.5.2(b)
Number of Cows across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
37
Table – 5.6
Economic Valuation of Herbs Marketed
Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Total
25 0 0 6
(158) (0) (0) (79)
(40) (40) (80) (160)
Source: Household Survey.
The average value recorded was around Rs.25 per month. Mostly households
having income 11,000 to 25,000 were involved in Maroorepicking.
e) Forest Product – Honey (Apiculture)
Both Avicennia marina and Rhizophoramucronatta are rich in nectar and
pollen on which honey bees can be reared. Khan (1999) has reported that
mangrove forest in Karachi coast produced 142 kg of honey during
May-June 1997.
Our sample survey shows that the production of honey per household per
month in the mangrove area was valued around Rs.9. The estimated value per
month in Keti Bunder area is around Rs.15 per month while the estimated
amount for Shah Bunder is approx. Rs.11 per month. Local people of Kharo
Chhan have not reported the production of honey in the area.
0
10
20
30
40
50
60
70
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.6
Economic Valuation of Herbs Marketed across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
38
Table – 5.7
Economic Valuation of Honey Marketed
(Rs./Household/Month)
Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Total
15 0 11 9
(66) (0) (38) (43)
(40) (40) (80) (160)
Source: Household Survey.
f) Habitat of Other Species: Crabs, Shrimps (on Site) and Shell Fish (off Site)
According to Khalil (1999) mangroves of Indus delta provide shelter for some
coastal species such as shrimps as well. Kahlil (1999) has reported that
Pakistan's shrimp fishery entirely depends upon the mangrove ecosystem.
Pakistan is earning some US $100 million annually from shrimp export.Our
sample survey also indicates huge economic dependence of household on
shrimps, crabs and shell fishes. On average households were earning
approximately Rs.20,175 per month (2997 from crabs + 13946 from shrimps +
3232 from shell fishes). The value is highest for the shrimp catch in Keti
Bunder (approx. 27,378 per month) while households of Shah Bunder and
Kharo Chhanwere earning around Rs.10,000 per month from the shrimp catch.
People of Keti Bunder were also earning approx. Rs.10,000 per month from
the sale of shell fishes as well (Table 5.8).
0
20
40
60
80
100
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.7
Economic Valuation of Honey Marketed across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
39
Table – 5.8
Economic Valuation of Crabs and Shrimps Marketed (on Site) (Rs.)
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder
Crabs Shrimps Crabs Shrimps Crabs Shrimps Crabs Shrimps
Total
5218 27378 2630 9458 2070 9474 2997 13946
(10608) (55296) (5209) (20823) (4345) (25859) (6734) (35343)
(40) (40) (40) (40) (80) (80) (160) (160)
Note: For details, see Annexure Tables.
Source: Household Survey.
0
5000
10000
15000
20000
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.8(a)
Economic Valuation of Crabs Marketed (on Site) across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
0
10000
20000
30000
40000
50000
60000
70000
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.8(b)
Economic Valuation of Shrimps Marketed (on Site) across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
40
The situation is not much different for sale of crab as well. People of Keti
Bunder were on average earning around Rs.5000 per month from the sale of
crab. People of KharoChhan reported were earning almost Rs.2600 per month
while the people of Shah Bunder were earning only Rs.2000 per month from
the sale of crab. Overall these species were almost entirely dependent on
mangrove ecosystem in the Indus delta.The estimated economic value of
mangroves was around Rs.20,175 per month (Table 5.8).
In addition, the households also reported catch of shellfish from all these
talukas. The highest level of Rs.10,425 per month per household was reported
in Keti Bunder, followed by Rs.1,303 in Kharo Chhan and Rs.600 in Shah
Bunder. On the whole, the average value of shellfish for all talukas was
Rs.3,232 per household per month (Table 5.9).
Table – 5.9
Economic Valuation of Shell Fish (Rs.)
Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Total
10425 1303 600 3232
(63199) (2375) (2023) (31631)
(40) (40) (80) (160)
Note: Detailed tables annexed.
Source: Household Survey.
g) Recreation and Tourism
Mangrove ecosystem is famous for tourism and constitutes an important part
of world tourism. Estimates show that the number of international tourists has
reached to 940 million in 2010.Travel and tourism generates around 5 percent
of the gross domestic product of the global economic activity and an estimated
6 to 7 percent of the world’s jobs [UN World Tourism Organization (2010)].
International tourists mostly prefer coastal areas for visits. Wetland and
0
10000
20000
30000
40000
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.9
Economic Valuation of Shell Fish across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
41
Wildlife make them ideal locations for tourism.The incomegenerationfrom
ecotourism could be significant and could provide significant support to the
livelihoods to the local communities.Pakistan’s wetlands are locally and
globally attractive. There are 19 sites of wetlands that have international
importance (these sites are designated as internationally important by the
Ramsar Convention in 2002).These sites although provide good attraction for
tourists but are currently not well developed for international tourism
purposes. Therefore a vast majority of the area has very small recreational
value. Table 5.10 shows among the household surveyed that almost 401
persons responses whowere that householdswere visiting mangrove forest for
bird watching, fish and shrimps viewing and for recreation purposes only.
Specifically 81% of the households visit mangrove to view fish and shrimps,
around 78% for recreation/enjoyment and around 91% visits mangrove area
for bird watching (Table 5.10).
Table – 5.10
# People Visiting Mangroves Area in All Talukas
# People Visiting Mangroves for: No Yes Don’t Know
Fish & Shrimp Viewing 25 130 5
Recreation 28 125 7
Bird Watching 12 146 2
Source: Household Survey.
In the absence of the reported data the analysis was based on the available
information gathered through field visits. As one household can visit
mangrove area for multiple purposes, the average of the visits to came up with
an average number of 134 households (i.e. almost 84%) of household visiting
mangrove forest. Assuming that the tourism is the major source of income for
the coastal community, estimated cost of visiting mangrove using the market
price/cost was estimated as follow:
Average Value of Visiting Mangrove = Number of visitors * (entrance fee +
Fuel Cost + food expenditure + any
other expenditure)
Table – 5.11
Costs Incurred in Visiting Mangroves (Based on Sample Households)
(Rs.)
Average Cost
Keti Bunder
Kharo Chhan
Shah Bunder
Fuel Cost 810 1201 1078 479
Permit cost 4 3 3 5
Food Expenditure 376 685 364 228
Other Expenditure 49 56 85 28
Source: Household Survey.
42
The cost of visiting mangrove was considered here as the income generated
from the ecotourism. The estimated travel cost of tourism mentioned in table
5.11 is based on the sample survey. In order to estimate the overall amount for
the whole community the economic value was estimated. Table 5.12 explains
the details.
Table – 5.12
Costs Incurred in Visiting Mangroves (Projected at Taluka Level)
(Rs./Month)
Talukas Total Keti
Bunder Kharo Chhan
Shah Bunder
A) # Household 3,989 3,654 10,915 18,558
B) Average # Household Visiting
Mangrove Forest (84% of the total) 3,351 3,069 9,169 15,588
Cost of Visiting Mangrove Forest
C) Fuel Cost 1,201 1,078 479 919
D) Permit cost 3 3 5 4
E) Food Expenditure 685 364 228 426
F) Other Expenditure 56 85 28 56
Ecotourism Value (B*(C+D+E+F)) 6,517,695 4,695,570 6,785,060 21,901,140
Source: Household Survey.
Table 5.12 shows that current value of ecotourism in all talukas in mangrove
area was around Rs.22,000. The value was highest for the Shah Bunder area
while lowest for the Kharo Chhan area.
h) Education and Research
Mangrove sites around the world attract a lot of researchers, students and
school classes who want to learn more about this intertidal habitat.
Kairoet al.(2009) and Spurgeon (2002) used value of fundingperstudents to
evaluate the value of mangrove for education and research. We this studythe
amount of funding for Ph.D, M.Phil and M.Sc. awarded by HEC to quantify
the research and education value of the mangroves was used.For that the data
of student doing Ph.D, M.Phil.and M.Sc. on mangroves was utilized. As there
is no published data available, different departments of Karachi University
were contacted to come up with a number of students working on mangroves.
This number was multiplied to the amount of scholarship provided by HEC to
come up with the economic value of mangrove.
PhD = 5 * Rs.10,000per Month
M.Phil = 3 * Rs.5,000per Month
Total value = Rs.65,000 per month.
The funding and research value per month was therefore Rs.65,000. It is,
however, acknowledged that the figure could be under estimated as the exact
number of students studying mangrove could be higher.
43
5.2.2 Indirect Value
a) Support to Fishing
The coastal area of the Indus delta is largely underdeveloped. The local
community depends on fishing and traditional profession. Higher returns
from fishing also result in attracting more people in fishing. The growth in the
sector is also due to the government policy to incraese revenue from the export
of fishes and high quality shrimps.
As the fish catch in the Indus delta is highly dependent on the mangrove
ecosystem, the importance of mangrove in sustaining the productivity of
on-shore and off-shore fisheries cannot be ignored. The review of literature
points out that mangrove forest is serving as breeding grounds for about 200
fish species. The household survey data shows 92 households, out of a total of
160, involved in fishing. The mangrove ecosystem supports production of
fishes of approx. Rs.29,542 per month. Monthly income estimated includes
value of fish used domesticaly and commercialy sold. Avearge value was
higher for Keti Bunder (Rs.63,382 marketed + Rs.2,149 non maketed = 65,
531) while lowest for Shah Bunder (Rs.8060 marketed +Rs.1351 non
marketed = Rs.9411 per month).
Moreover, average mangrove value of fish catch for domestic use was
estimated across different income groups i.e. subsistence (income less than
10,000), poor (income between 11,000 to 25,000), medium (income between
26,000 to 50,000) and rich household (more than 50,000) the estimated levels
were Rs.1113/month, Rs.2033/month, Rs.2227/month and Rs.6116/month,
respectively (Table 5.13). (For details, see Appendix Table 5.13).
Table – 5.13
Economic Valuation of Benefits Marketed and Non-Marketed Fish Catch
(Rs./Household/Month)
Keti Bunder Kharo Chhan Shah Bunder Total
Non-Marketed
Marketed Non-
Marketed Marketed
Non-Marketed
Marketed Non-
Marketed Marketed
Total
3913 29900 2149 63382 1351 8060 2191 27351
(4526) (73494) (2483) (301836
) (1603) (16548) (2986)
(155958
)
(40) (40) (40) (40) (80) (80) (160) (160)
Note: For greater details, see appendix table).
Source: Household Survey.
44
b) Shoreline Protection - Buffer to Cyclone
The literature identifies the presence of mangrove forest especially Avicennia
marina to ensure the firm and stable formation of shorelines. The term
shoreline protection is, not clearly defined. The term can refer to either
protection from soil erosion or protection from sea cyclone/tsunamis and
storms. In this study we have focused only on the valuation of mangroves as
protection against extreme weather events such as tsunamis, sea cyclones or
hurricanes.
The valuation of mangrove forest as an instrument for shoreline protection is a
complex subject. The most widely used technique is the Replacement Cost
Technique. For this technique the value of a man-made seawall is derived
having the same protective effect for the shoreline. The value is then applied
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.13(a)
Economic Valuation of Benefits Marketed across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
0
2000
4000
6000
8000
Subsistence Low Middle High
Ec
on
om
ic V
alu
e (
Rs
.)
Income Levels
Figure - 5.13(b)
Economic Valuation of Benefits Non-Marketed across Income Categories
Keti Bunder Kharo Chhan Shah Bunder
45
to the mangroves (Kairoet al.2009, Spurgeon 2002). The alternate method is
the “Damage Cost Avoid Technique”. This calculates potential damage of a
sea cyclone if mangroves did not exist (Ruitenbeek, 1992).
History of sea cyclone in Pakistan shows that Pakistan first experienced an 8.7
magnitude earthquake in Makran coast in 1945. It resulted in a huge tsunami
in the Arabian Sea and killed more than 4,000 people. Second deadly storms
hit Karachi coast in 1965, causing 10,000 casualties. In 1999, another cyclone
killed 6,200 people after making landfall at Shah Bunder.It was, thus, assumed
that there is only 10% likelihood for a sea cyclone to hit coastal areas in next
20-30 years, given its increased frequency in recent years. Around 18,558
houses having average price equalsRs.500,000 and assuming an additional
protection of 73 per cent, the shoreline protection value of the mangroves was
estimated as follows outlined in Table 5.14(a).
Table – 5.14(a)
Estimation of Value Shoreline Protection at Sampled Population Level (Rs.)
Based on Sample Population Keti
Bunder Kharo Chan
Shah Bunder
Total
A. Number of houses 40 40 80 160
B. Average house price 600,000 400,000 500,000 500,000
C. Average Value of other assets 240,000 160,000 200,000 200,000
D. Total Value of household assests 840,000 560,000 700,000 700,000
E. Value of houses (Rs.) (A*D) 33,600,000 22,400,000 56,000,000 112,000,000
F. Likelihood of severe weather event 10% 10% 10% 10%
G. Value of protection (E*F*0.73 ) Rs. 2,452,800 1,635,200 4,088,000 8,176,000
H. Value per Month Rs. (G/12) 204,400 136,267 340,667 681,333
Source: Household Survey.
Table – 5.14(b)
Taluka Wise Projection of Values of Shoreline Protection (Rs.)
Based on Projection at Taluka Level
Keti Bunder
Kharo Chan
Shah Bunder
Total
A. Number of houses 3,989 3,654 10,915 18,558
B. Average house price 600,000 400,000 500,000 500,000
C. Average Value of other assets* 240,000 160,000 200,000 200,000
D. Total Value of household assets 840,000 560,000 700,000 700,000
E. Value of houses (Rs.) (A*D) 335,076,0000 204,624,0000 764,050,0000 12,990,600,000
F. Likelihood of severe weather event 10% 10% 10% 10%
G. Value of protection (E*F*0.73 ) Rs. 244,605,480 149,375,520 557,756,500 948,313,800
H. Value per Month Rs. (G/12) 20,383,790 12,447,960 46,479,708 79,026,150
I. Value per Month per household Rs. 5,110 3,406 4,258 4,258
J. Area Mangroves (ha) 7,241 8,133 39,347 54,721
K. Value shoreline protection
/hac/month (H/J) 2,815 1,531 1,181 1,444
Source: Household Survey.
46
e) Carbon Storage and Fish Biomass
U.N. (1996) reports on the level of productivity and carbon fixation (in terms
of grams of carbon fixed per square meter per day) in Arabian Sea. It reveals
that the Arabian Sea is on top of the world with a carbon fixation of 1.5-1.8
gC/m2/day which is 10 times the world ocean and 4 times the average values
of the Indian Ocean (Reference Ryther and Menzel, 1964). Though the daily
estimates on carbon fixation occasionally reaches a level of 5 gC/m2/day in
some oceans but the comparison across oceans are based on averages where
the Arabian Sea appears to be the most productive.
The report quoting the same reference also claims that the Arabian Sea shows
an equivalence of 9.4 million ton of fish biomass in the EEZ of Pakistan. It,
however, needs to be noted with the care that the productivity of the Arabian
Sea is not distributed evenly. The Gulf of Oman has the highest productivity
of fish biomass when compared with other parts of the Arabian Sea.
Economic Perspective (2003) highlights the challenges faced at the World
level due to overfishing and the world leaders concerns. The 25th meeting of
the FAO’s Committee on Fisheries (COFI) and World Summit on Sustainable
Development at Johannesburg in 2002, while expressing world leaders
acknowledgement of the vital role of marine fisheries to economic and food
security and to biodiversity in general, showed its concerns:
“to maintain or restore stocks to levels that can produce maximum sustainable
yield with the aim of achieving these goals for depleted stocks on an urgent
basis and where possible not later than 2015”.
The paper also expresses concerns in the light of UNCED’s Agenda 21 which
pointed out that 50 percent of world population lived within 60 kilometers of
coasts in 1992 and by 2020 this proportion would increase to 75 percent. That
likely upward change will put all living and non-living resources in coastal
zones under increasing pressure.
5.2.3 Non Use Value
The estimated non-use values were based on willingness to pay (WTP)
method.Specifically, it shoedhow much local community is willing to pay for the
conservation, protection and development of the mangroves forest. This expresses the
intrinsic value of mangroves. The value is the acknowledgement of the existence of
the mangroves in the ecosystem (Ghani, 2006).
47
Table – 5.15
Type and Nature of Community Willingness to Participate (# Households)
Community Willing to Participate
Total Keti Bunder Kharo Chhan Shah Bunder
As Wage Labour 112 27
(67.5%)
27
(67.5%)
58
(72.5%)
As Voluntary Labour 39 12
(30%)
13
(32.5%)
14
(17.5%)
Not Willing to Contribute 9 1
(2.5%) 0
8
(10%)
Total 160 40 40 80
Source: Household Survey.
Table – 5.16
Estimation of WTP Based on Descriptive Analysis
(Rs./Household/Month)
Total
Keti Bunder
Kharo Chhan
Shah Bunder
A. Household visited 160 40 40 80
B. % Household willing to pay (WTP) 25 30 33 18
C. # days per month willing to work 3 4 2 2
D. Average daily Wages in the Village 250 250 250 250
E. WTP (Rs./month) - C*D 750 1000 500 500
F. Total number of Houses 18558 3989 3654 10915
G. Area of mangroves (ha) 54721 7241 8133 39347
H. # of household willing to pay 4453.92 1196.7 1187.55 1910.125
I. Total value (Rs/month) - H*E 3340440 1196700 593775 955063
J. Value of mangroves (Rs./ha/Month) - I/G 61 165 73 24
Source: Household Survey.
Tables 5.15 and 5.16 provide estimate on the amount community was willing to pay.
This was the income they were willing to sacrifice for providing the services. During
the fields survey it was specifically askedfrom each household as to how many days
per month they will be willing to work voluntarily. This led to the computationof the
income on daily basis in estimating the income each household werewilling to forgo
in providing labour for the development of mangroves. This forgone income was
taken as the amount they were willing to pay. Table 5.16 shows that out of the 160
household surveyed 25% were willing to pay for the conservation of mangrove forest.
The total amount of the households willing to pay was around Rs.30,000 per month
[160x0.25x750]. By projecting the amount for the overall households in the three
talukas, we estimated an overall economic value of mangrove around Rs.3,340,440
per month per household. However the computation is based on the descriptive
analysis only while literature has identified a number of techniques to compute the
amount community is willing to pay. One such technique is already outlined in an
earlier section on methodology using Tobit model.
We also estimated the regression model using Tobit model to compute WTP. Results
are reported in Tables 5.17 and 5.18.
48
Table 5.17 shows positive and significant effects of the amount household were
willing to pay. This shows that the community was motivated significantly for the
conservation of the mangrove forest. On average, a household was willing to pay
around Rs.2,518 per month for the protection and development of mangrove forest.
Keti Bunder being the more economically developed taluka among the three talukas
surveyed, shows that each household was willing to pay around Rs.4,145 per month.
In contrast to the households of Keti Bunder, households of Shah Bunder, being more
deprived than the rest of the two, shows low willingness to pay (approx.2,177 per
month per household).(Table 5.18).
Table 5.17 also shows significant and positive effect of ownership of livestock on the
household willing to participate for the conservation and development of mangroves.
The reason is straight forward, householdshaving livestock directly dependent on
mangroves for the fodder. However the effect is not significant for Keti Bunder. For
Keti Bunder availability of electricity and per capita household income shows
significant but negative effect. For Kharo Chhan agriculture land ownership shows
significant and negative effects while the effect of agriculture land ownership is
positive and significant for Shah Bunder.Overall goodness of fit test indicates that our
model was not a weak model and explained almost 20 percent of the variation in the
dependent variable.
Table – 5.17
Total Keti Bunder Kharo Chhan Shah Bunder
Coef. T-Stats Coef. T-Stats Coef. T-Stats Coef. T-Stats
Amount Willing to
Pay 0.0004 6.4* 0.0003 3.15* 0.0004 2.97** 0.0004 4.69*
Family Size -0.0051 -0.96 -0.01 -1.11 -0.01 -0.94 -0.008 -0.83
Highest Education
Completed -0.0007 -0.07 -0.02 -0.84 -0.0004 -0.02 0.003 0.18
Log per Capita
Household Income -0.045 -1.27 -0.11 -2.4** 0.008 0.07 -0.09 -1.36
Agriculture land
Own -0.001 -0.5 0.02 0.87 -0.003 -1.6*** 0.004 2.27*
Ownership of
Livestock 0.156 2.1** 0.34 1.53 0.239 1.7*** 0.19 1.75***
Ownership of
House -0.110 -1.51 0
0
-0.17 -1.6***
Availability of
Electricity -0.049 -0.59 -0.33 -2.6** 0.11 0.49 0.01 0.04
Availability of Gas 0.196 1.09 0
0
0.19 0.51
Constant 0.970 3.93* 1.85 4.36* 0.52 0.65 1.23 2.61**
Log likelihood -105.6 -12.0 -24.8 -58.1
F-stat 5.23 1.62 2.34 3.1
Prob. > chi2 0.00 0.166 0.047 0.003
Number of obs. 160 40 40 80
left-censored obs. 32 5 8 19
Pseudo R2 0.20 0.48 0.24 0.19
Source: Household Survey.
49
Table – 5.18
Willingness to Pay on Household Level (Rs.)
Amount Household Willing to Pay (Rs./Month)
Total Keti
Bunder Kharo Chhan
Shah Bunder
Mean WTP = (1/B1) * ln [1+eβ0+∑βiXi] 2,518 4,145 2,362 2,177
Source: Household Survey.
5.3 Derivation of Total Value of Mangroves Forest
In determining the total valuation of mangroves, issues such as number of non-timber
forest products, recreation and tourism, education and research were considered in
addition to support to fish and shoreline protection, willingness to pay to protect
mangroves. A detailed account of such benefits at the level of sampled households has
been presented in Table 5.19.
Table – 5.19
Valuation of Mangrove per Household per Month
(Rs./Household/Month)
Keti
Bunder Kharo Chhan
Shah Bunder
All Talukas
BENEFITS (Per Household per Month)
Fuel Wood 1,585 900 1,446 1,344
Wood for Poles and Housing 300 198 173
Animals Browsing 3,632 2,200 4,732 9,864
Herbs & Medicine 25 - - 6
Honey (Apiculture) 15 - 11 9
Habitat for Other Species 43,021 13,391 12,144 20,175
Recreation and Tourism 1,634 1,285 622 1,180
Education and Research - - - 3.5
Support to Fish 33,815 65,531 9,411 29,542
Shoreline Protection 1,460 1,095 1,278 1,278
Carbon Storage - - - -
Amount Willing to Pay 4,145 2,362 2,177 2,518
Total Benefit of Mangroves 89,332 87,064 32,019 66,093
COST (Per Household per Month)
Fuel Cost 36,037 32,350 14,381 28,287
Permit Cost 87 78 142 113
Depreciation 7,065 6,587 3,247 5,037
Food Cost 20,557 10,927 6,835 11,287
Others (15% of the Total) 9,562 7,491 3,691 6,709
Total Cost of Mangroves 73,308 57,433 28,296 51,433
Total Economic Value 16,024 29,631 3,723 14,660
50
The table also provides cost estimates in acquiring those forest products mentioned
above. It shows an economic value of Rs.14,660 per household per month for the 160
sampled households.
The estimates made at the sampled household level were projected at the taluka level
keeping in view the total number of households and total area under mangrove in each
of the three talukas.
The valuation of mangrove was further classified into marketed (Rs.48,454) and
non-marketed (Rs.17,839) values.Table 5.20 provides disaggregated levels of
valuation across on-site and off-site activities. It also shows levels of indirect benefits
and other benefits i.e. non-use values.
Table – 5.20
Levels of Benefit
(Rs./Household/Month)
Benefits (Use Value) On-Site Off-Site
Marketed (Direct Use)
Fuel Wood (Rs./Month) 549
Wood for Poles and Housing (Rs./Month) 173
Herbs & Medicine(Rs./Month) 6
Habitat for Other Species (Rs./Month) 17,984
Support to Fish (Rs./Month) 29,542
Sub-Total (Marketed) 18,712 29,542
Non-Marketed (Indirect Use)
Shoreline Protection (Rs./Month) 1,278
Animals Browsing (Rs./Month) 9,864
Fuel Wood (Rs./Month) 795
Honey (Apiculture) (Rs./Month) 9
Habitat for other Species (Rs./Month) 2,191
Sub-Total(Non-Marketed) 14,137
Other Benefits(Non-Use Value)
Recreation and Tourism (Rs./Month) 1,180
Education and Research 3.5
Amount Willing to Pay (Rs/Month) 2,518
Sub-Total (Other Benefits) 3,702
Total(Marketed and Non-Marketed) 66,093
It implies that at sampled household level, a total valuation of Rs.66,093 per month
which carries a share of 73.0 percent (for marketed and 21.4 percent of non-marketed
part), and 5.6percent as non-use values.
Table 5.21 summarizes the entire analysis on the valuation of mangroves presented in
earlier sections. It explains the way the valuation of Rs.66,093pr household per month
was projected at the taluka level (i.e. all three talukas taken jointly) keeping in view
the estimated number of 18,558 households. It shows an annual level of Rs.14.719
billion for all talukas level. The table initially shows levels of aggregate benefits (i.e.
all benefits directly, indirectly and non-use values) in sub-section A.
51
In sub-section B, it portrays the levels of costs and shows an annual level of costs as
11.45 billion rupees.
In sub-section C, it shows an estimated level of values of $ 1,762 per household per
yea, and $ 597 per household per hectare of mangrove area.
Tables – 5.21
Computation of Total Benefits and Cost at Aggregate Level (Rs./Month)
A. Gross Benefits
Gross Benefits/Household/Month(Rs.) 66,093
# of Households 18,558
Gross Benefits at Aggregate Level/Year (Rs. Billions) 14.719
Gross Benefits at Aggregate Level/Year(US$ Millions) 147.19
Gross Benefits at Aggregate Level/Household/Year(US$ Millions) 7,931
Forest Area of Mangroves(Hectares) 54,721
Gross Benefits at Aggregate Level/Hectare/Year(US$) 2,690
B. Aggregate Cost
Aggregate Cost/Household/Month (Rs.) 51,433
# of Households 18,558
Aggregate Cost/Year (Rs. Billions) 11.45
Aggregate Cost/Year(US$ Millions) 114.50
Aggregate Cost//Household/Year(US$ Millions) 6,171
Forest Area of Mangroves (Hectares) 54,721
Aggregate Cost//Hectare/Year(US$) 2,093
C. Ratio (B–A)
Net Value/Household/Year (US$) 1,762
Net Value/Hectare/Year (US$) 597
5.4 Comparative Estimates on Valuation of Mangroves
The valuation of mangroves presented in the preceding section was compared with
other estimates made for similar mangroves regions.
Table – 5.22
Comparative Estimates on Valuation of Mangroves (in US$)
Source Year Country Estimation of Benefits
Per Household/Year Per Hectare/Year
1. Sathirathi 2000 Thailand 1,422 239
2. IUCN 2007 Sri Lanka 1,171 -
3. UNEP 2011 Kenya 1,092 840
4. IUCN 2013 Pakistan 1,762 597
Source: Various Reports (including this study).
Table 5.22 presents a comparative statement highlighting valuation estimates on
mangroves in different regions. The current study’s estimates were US$ 597 per
hectare of mangrove per year. Similarly, the estimated value per household per year
52
was US$ 1,762. Those estimates on annual level seem consistent with other regions if
the time factor is taken into account.
Another reason for somewhat higher estimate on Pakistan’s mangroves could be
related to the fact that the Arabian Sea is considered a highly productivity region for
biomass of fishing which is 10 times the world average and 4 times that of the Indian
Ocean.
Nevertheless, these levels of valuation indicate the potentials reposed, and efforts are
needed to make the region’s potentials sustainable in the long run. The amount of
efforts, resources and in-depth scientific work that would be required can hardly be
overemphasized.
5.5 Distribution of Total Economic Benefits of Mangroves Annually
Figure – 5.5.1
Distribution of Total Economic Benefits of Mangroves
Total Economic Benefits
$ 147.2 Million
Use Values $139 Million
Non-Use Values
$8.2 Million
Direct Benefits $107.5 Million
Indirect Benefits $31.5 Million
Eco-Tourism $2.6 Million
WTP $5.6 Million
53
The Flow Chart 5.5 shows distribution of total benefits into use values and
non-use values. Within use values, it decomposes into direct and indirect
benefits. Similarly, in case of non-use values it splits into assumed benefits of
eco-tourism and willingness to pay.
In proportional terms, the direct benefits tend to dominate by exercising a
share of 73 percent of the total value of benefits. The indirect benefits had a
share of 21.4 percent, followed by eco-tourism 3.8 percent. The anticipated
benefits through community’s willingness to pay (participate), for voluntary
work in planting mangroves and its future development, accounting for 1.8
percent of total benefits.
5.6 Derivation of Benefit-Cost Ratio and IRR
Based on the estimates on costs and benefits derived from mangrove forest presented
earlier, the economic analysis focused on the derivation of benefit-cost ratio and
internal rate of return on the plantation of 10,350 hectares by Sindh Forest
Department (SFD) in the Indus Delta under Sindh Costal Community Development
Project (SCCDP).
It would not be irrelevant here to mention the broadly defined benefits received by the
local community under the mangrove plantation. These direct benefits include:
a) employment of nearly 40,000 man days of paid labour in plantation and
maintenance (i.e. replantation to increase success rate).
b) 518 boat days employed in transporting hired labour to the area of plantation.
This activity produced significant income earnings for the boat owners in the
area.
c) employment of 8 guards for the up keep of planted area.
Willingness to Pay 1.8%
Eco-Tourism 3.8%
Indirect Benefits
21.4%
Direct Benefits 73%
Flow Chart - 5.5.1
Distribution of Total Economic Benefits of Mangroves Annually
54
d) employment of IUCN staff comprising supervisors and field assistants.
e) establishment of base camps in the area that provided further income and
employment opportunities in the area.
These above mentioned benefits were measured in the light of the information
provided by IUCN and SCCP directorate. In addition, the detailed estimates on net
valuation of benefits (on a per unit basis) estimated under the study were added to
streamline the annual costs incurred and benefits likely to be received under the
plantation of mangroves under SCCDP.
The SF department carried out the plantation work on 10,350 hectares during the five
year period i.e. 2009-2013. During the period, the success rate was reported at 96
percent in Shah Bunder taluka and 100 percent in Keti Bunder taluka (Monitoring &
Evaluation Report of IUCN, June 2013). Based on this, it is expected that there exists
a higher possibility of success.
Benefit-Cost Ratio
In view of above, derivation of benefit-cost ratio and internal rate of return were
carried out to judge the economic significance of such interventions.
Table 5.23 describes the streams of costs and expected benefits related to mangrove
plantation. The costs are spread over evenly through the first five years of the activity.
Since mangrove plants take longer in providing the benefits, the stream of benefits
was assumed to start from the 15th
year onwards to 30th
year.
Keeping in view the initial fixed costs and net present worth of future benefits (using
an annual discount rate of 10 percent), the activity shows a benefit-cost ratio of 3.56
which is quite significant. It is a conservative estimate and the real benefits may
exceed and thereby would increase the profitability even further. As a note of caution,
however, it must be stressed that such a success depends on higher survival rate as
well as protection of forest from the pressures of human actions i.e. a sustainable
development of mangroves appears as the necessary condition in achieving higher
levels of benefits.
Internal Rate of Return (IRR)
In order for any activity to be acceptable (i.e. bankable) for investment, it is always
necessary to compute internal rate of returns. Based on the flows of cash during the
expected life of the project/activity, as discussed earlier, an implicit rate of interest of
10 percent annually was used in deriving IRR.
An IRR of 25 percent was estimated which provides sufficient capacity for the
investment to take place.
55
Table – 5.23
Computation of Benefit-Cost Ratio on Mangrove Plantation under SCCDP (in US$)
Annual Cost Year 1 to
Year 5 Year 15 Year 16 Year 17 Year 18 Year 19 to Year 26 Year 27 Year 28 Year 29 Year 30
A. Cost of Plantation US$ Area (Hectare) 2070 Plantation Cost /Hectare 99 Total Plantation Cost 204930
B. Cost of Maintenance @30% of Plantation Cost Area(Hectare) 621 Plantation Cost / Hectare 33 Total Plantation Cost 20493
C. Boat Cost Boat Days @ one boat covering 4 hectares 518 Boat Cost/day 140 Total Boat Cost 72520
D. Cost of Guard (8 Guards @$150/month) 14400 E. IUCN (Cost of Supervisor & Field Assistance) 11400 F. Base Camp Cost @ One Percent of Cost of A,B,C,D 3123 C. Total Cost (A+B+C+D+E+F) 326866 D. Benefits of Mangroves US$
Area(Hectare) 2070 2070 2070 2070 2070 Benefits /Hectare (as per estimated of $722/year/hectare) 722 722 722 722 722 Total Benefits US$ 1494540 1494540 1494540 1494540 1494540
1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 1494540 2989080 4483620 5978160 7472700 8967240 7472700 5978160 4483620 Total Gross Benefits (Net Present Value @10 % annually) 5,824,194.92 Total Cost 1,634,330.00 Benefits Cost Ratio 3.56
56
Table – 5.24
Derivation of Internal Rate of Return (IRR) on Mangrove Plantation under SCCDP
(in US$)
(A)
Cash Outflow
(B)
Cash Inflow
(C)
Cash flow (B-A)
Year1 326,866 0 -326,866
Year2 326,866 0 -326,866
Year3 326,866 0 -326,866
Year4 326,866 0 -326,866
Year5 326,866 0 -326,866
Year6 0 0 0
Year7 0 0 0
Year8 0 0 0
Year9 0 0 0
Year10 0 0 0
Year11 0 0 0
Year12 0 0 0
Year13 0 0 0
Year14 0 0 0
Year15 0 1,494,540 1,494,540
Year16 0 2,989,080 2,989,080
Year17 0 4,483,620 4,483,620
Year18 0 5,978,160 5,978,160
Year19 0 7,472,700 7,472,700
Year20 0 7,472,700 7,472,700
Year21 0 7,472,700 7,472,700
Year22 0 7,472,700 7,472,700
Year23 0 7,472,700 7,472,700
Year24 0 7,472,700 7,472,700
Year25 0 7,472,700 7,472,700
Year26 0 7,472,700 7,472,700
Year27 0 8,967,240 8,967,240
Year28 0 7,472,700 7,472,700
Year29 0 5,978,160 5,978,160
Year30 0 4,483,620 4,483,620
IRR 25%
57
CONCLUSIONS AND RECOMMENDATIONS
1. The on-site (i.e. coastal environment) is interrelated with off-site (open sea
environment) and jointly appear as a great natural resource on which the
coastal communities depend heavily for their livelihood.
2. However, if such an exclusive dependence continues in the long run, it may be
productive or unproductive for mangroves based on how this great natural
resource is valued by the coastal communities. Such an understanding (or lack
of it) would be pivotal to the long run sustainability of mangroves in the
region.
3. A number of Focused Group Discussions (FGD’s) were conducted to
understand the community relationship with mangroves. According to the
participants the reasons behind the reduction are: reduced supply of sweet
water and sediments, over cutting of mangroves for sale of timber, fuel wood
and poles for housing. Participants also criticized decision of the government
about restriction on the Indus water flows at Kotri barrage in 1960 and held
that responsible for the reduction in mangroves cover.
4. The average family size of all sampled households was 11.27, where the
minimum of 10.44 was for Shah Bunder and maximum of 13.55 for Kharo
Chhan. It is interesting to note that in Shah Bunder where the average family
size was lowest (i.e. 10.44), the average number of males (i.e. 3.46) was
higher than the average number of females (i.e. 3.21) and the associated
average number of children was lowest.
5. The scale of devastation in these coastal talukas as a result of continuous sea
intrusion has resulted in the loss of fertile agricultural land. Currently,
agricultural land ownership has reduced along the coastal belt of Indus delta.
Only a fraction of land holding is brought under cultivation owning to the fact
that the supply of fresh water has reduced considerably.
6. The ownership of livestock was limited in the area. Only 58 households out of
160 (i.e. 36 percent) were keeping livestock. The raising of camels was
reported only by 10 households with 7 from Shah Bunder.
7. A common view of the area reflects the fact that Keti Bunder has retained its
historical location as well as has acted as a center for various developmental
activities despite facing a number of threats in the form of natural as well as
man made disasters. In contrast, Shah Bunder could not sustain the devastation
of sea cyclone of mid 1990’s and as a result its taluka headquarter was shifted
to another location in the upstream area, its population was scattered and as
such currently the location of Shah Bunder’s proper settlement is lost to
antiquity. As a consequence, Shah Bunder has yet not reversed its position
undermining its fisheries catch and marketing and other economic
development prospects.
8. The fisheries as a source of income was highest in Keti Bunder where 29 out
of 40 households (72.5 percent) had it as primary occupation. In case of Kharo
Chhan it was 52.5 percent and in Shah Bunder it was 43.8 percent, of the
sampled households. The highest participation was in fisheries activities all
across.
58
9. Over 90 percent of the respondents reported visiting mangroves either
exclusively to collect forest products like fuel wood, fodder, catching fish
crabs, shrimps, honey, herbs, poles for use in house construction, animal
browsing, or to take rest and recreation while going towards open sea for
fishing.
10. Based on the responses of sampled households towards different socio-
economic aspects, it becomes clearer that local community heavily depends on
fisheries as their exclusive source of livelihood. The incomes are largely
generated from fishing whereas the non-fishing occupations generate over one
third of their incomes.
11. Sample survey also indicates huge economic dependence of household on
shrimps, crabs and shell fishes. On average households were earning
approximately Rs.20,175 per month (2997 from crabs + 13946 from shrimps +
3232 from shell fishes).
12. The study tends to portray the levels of benefits and costs to coastal
communities in carrying out their economic activities with particular reference
to mangroves.
13. It further shows that incomes from fishing are highest and central to all
activities related to the natural habitat within the ecosystem, where mangroves
position remains pivotal. The direct benefits amount to 73 percent of all
benefits.
14. In assessing the role of mangroves, the study focused on evaluation of all
benefits (direct, indirect), whether those were marketed on non-marketed. In
the process, it used a combination of primary and secondary data and reviewed
available literature.
15. The analysis also decomposed the total benefits into use and non-use values
which were 94.4 percent and 5.6 percent, respectively.
16. The analysis also reveals on-site benefits as 55.3 percent and off-site benefits
as 44.7 percent of the total benefits. It showed a relatively larger dependence
of coastal communities towards on-site activities in relation to off-site
activities.
17. The socio-economic profiles of the coastal communities, as observed through
the sample survey, reflect extreme levels of social poverty. With an average
family size of 11.27, over 60 percent of head of households illiterate, lack of
safe drinking water (only 6 percent of households with piped drinking water),
75 percent without electricity, dilapidated road structure and 48 percent living
in huts, provide ample evidences to suggest extreme levels of poverty in the
Indus delta.
18. The demographic characteristics also reveal higher family size associated with
larger number of adult females (in relation to adult males). This could be one
of reasons for higher family size.
19. The pattern of economic activities reveal that, on average, one child out of ten
in each household was in the primary occupation, reflecting another dimension
of poverty in the area.
59
20. In each of the three sampled talukas, fishing was the dominating occupation
i.e. in Keti Bunder 72.5 percent, Kharo Chhan 52.5 and 43.8 percent at Shah
Bunder had fishing as their primary occupation.
21. The females in the area have no primary occupation which could generate
incomes of the family. They, however, participate in the secondary
occupations.
22. The direct cash income levels per month, as revealed by the sampled
households, shows that on average, those having fishing as primary occupation
earned Rs.42,843 per month and Rs.4,728 if fishing was a secondary
occupation. Similarly, those households who had non-fishing as primary
occupation earned, on average, Rs.20,172 per month and Rs.57,393 per month
in the event they had non-fishing as secondary occupation.
23. On the whole it appears that these revealed income levels may not suggest
abject poverty in the area from a financial point of view. However, the social
indicators highlighted above, do tend to verify significant levels of social
poverty among the coastal communities of Indus delta.
24. The study uses multivariate techniques to estimate willingness to pay
(participate) from the communities towards the development of mangroves
forests. As part of non-use values, estimation of benefits of tourism was also
conducted which tends to show dependence of coastal communities on
mangroves.
25. The study estimates total valuation of mangroves at Rs.14.7 billion rupees
annually i.e. US$ 147.2 million. The net valuation per hectare of mangroves
per annum was estimated at Rs.59,700 (or US$ 597), and a net valuation of
Rs.176,200 per household per annum (i.e. $ 1,762).
26. The potentials reposed, no matter how big they may appear, refer to the
“crude” values of products mangroves tend to offer in addition to the valuable
services in protecting not only the coastal communities but the entire coastal
area. The situation that arises calls for significant measures required not only
in the conservation and development of mangroves but also towards the
modernization and value addition of the products offered by mangroves.
27. In the broader context based on the findings of this study and a significant lack
of overall economic development in the Indus delta, there is a clear need that
the area be given exclusive attention. By considering the fact that increased
storage of irrigation water in the upstream for agricultural growth has tended
to significantly reduce the flow of sweet water and silt into the deltaic region
thereby extensively damaging the mangroves over time, the need for
compensation to the coastal communities seem fully justified. In addition, the
untreated industrial effluents thrown into the Arabian sea has also damaged
mangroves considerably (through eutrophication). In the obtaining situation,
not only the coastal communities but the entire coastal belt of the Indus delta
has been exposed to threats from the sea. In the light of international
conventions, agreements and framework, it is suggested that 0.10 percent of
annual value added of agricultural and manufacturing sectors be allocated
towards the conservation and development of natural habitat, and the
economic uplift of coastal communities of the Indus delta. At current prices,
such an allocation would be equivalent to Rs.10 billion annually.
60
28. The economic analysis of the study reveals a benefit cost ratio of 3.56 which is
quite significant.
29. The analysis also reveals an internal rate of return IRR of 25 percent which is
considered suitable for investments.
61
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63
Annexure Tables
Annexure Table – 5.1
Economic Valuation of Fuel Wood (Marketed) acrossIncome Categories
(Rs.)
Monthly Income Levels
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder
Subsistence (Less than 10,000)
300* 313 726 545
(949)** (677) (1687) (1375)
(10)*** (16) (34) (60)
Low (11,000 to 25,000)
875 783 653 730
(1408) (842) (1546) (1396)
(16) (12) (38) (66)
Middle (26,000 to 50,000)
- 333 833 467
- (816) (2041) (1356)
(3) (6) (6) (15)
High (Higher than 50,000)
- - - -
- - - -
(11) (6) (2) (19)
Total
425 410 681 549
(1059) (732) (1609) (1308)
(40) (40) (80) (160)
Note: *, ** and *** are Value, Standard Deviation and # Observations, respectively.
Source: Household Survey.
64
Annexure Table – 5.2
Economic Valuation of Fuel Wood Non-Marketed (Household Consumption) across Income Categories
(Rs.)
Monthly Income Levels
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder
Subsistence
880 325 300 403
(1135) (809) (790) (871)
(10) (16) (34) (60)
Low
1756 700 1189 1238
(1489) (1217) (2177) (1892)
(16) (12) (38) (66)
Middle
1 500 967 587
(1) (1225) (1211) (1095)
(3) (6) (6) (15)
High
864 500 - 658
(1583) (1225) - (1375)
(11) (6) (2) (19)
Total
1160 490 765 795
(1444) (1038) (1665) (1487)
(40) (40) (80) (160)
Source: Household Survey.
Annexure Table – 5.3
Economic Valuation of Wood for Pole and House Construction across Income Categories
(Rs.)
Income Levels
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder Pole
Marketed Wood for Housing
Pole Marketed
Wood for Housing
Pole Marketed
Wood for Housing
Pole Marketed
Wood for Housing
Subsistence
- - - - - - - -
- - - - - - - -
(10) (10) (16) (16) (34) (34) (60) (60)
Low
- - 250 500 279 105 206 152
- - (866) (1446) (1623) (649) (1280) (789)
(16) (16) (12) (12) (38) (38) (66) (66)
Middle
- - - - 200 - 80 -
- - - - (490) - (310) -
(3) (3) (6) (6) (6) (6) (15) (15)
High
- - 500 - - - 158 -
- - (1225) - - - (688) -
(11) (11) (6) (6) (2) (2) (19) (19)
Total
- - 150 150 148 50 111 62
- - (662) (802) (1125) (447) (861) (510)
(40) (40) (40) (40) (80) (80) (160) (160)
Source: Household Survey.
65
Annexure Table – 5.4
Camel Population in Mangrove Forest Area
(#)
Talukas Cattles
# Camels # Buffaloes
Keti Bunder 1,006 375
Kharo Chhan 1,802 894
Central Shah Bunder 1,823 815
East Shah Bunder 1,197 835
Total 5,828 2,919
Source: Household Survey.
Annexure Table – 5.5.1
Number of Goats and Camels across Income Categories
(#)
Income Levels
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder
# Goats #
Camels # Goats
# Camels
# Goats #
Camels # Goats
# Camels
Subsistence 0 15 18 0 1 4 19 19
Low 0 0 9 2 5 42 14 44
Middle 6 0 0 0 0 0 6 0
High 10 15 0 0 0 0 10 15
Total 16 30 27 2 6 46 49 78
Source: Household Survey.
Annexure Table – 5.5.2
Numbers of Buffaloes and Cows across Income Categories
(# Animals)
Income Levels
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder #
Buffalos # Cows
# Buffalos
# Cows #
Buffalos # Cows
# Buffalos
# Cows
Subsistence 0 0 1 0 25 4 26 4
Low 0 0 15 6 29 13 44 19
Middle 3 0 1 0 4 0 8 0
High 20 10 0 8 0 3 20 21
Total 23 10 17 14 58 20 98 44
Source: Household Survey.
66
Annexure Table – 5.6
Economic Valuation of Herbs Marketed across Income Categories
Income Levels Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Subsistence
0 0 0 0
(0) (0) (0) (0)
(10) (16) (34) (60)
Low
63 0 0 15
(250) (0) (0) (123)
(16) (12) (38) (66)
Middle
0 0 0 0
(0) (0) (0) (0)
(3) (6) (6) (15)
High
0 0 0 0
(0) (0) (0) (0)
(11) (6) (2) (19)
Total
25 0 0 6
(158) (0) (0) (79)
(40) (40) (80) (160)
Source: Household Survey.
Annexure Table – 5.7
Economic Valuation of Honey Marketed across Income Categories
Income Levels Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Subsistence
30 0 7 9
(95) (0) (30) (45)
(10) (16) (34) (60)
Low
0 0 14 8
(0) (0) (44) (34)
(16) (12) (38) (66)
Middle
100 0 17 27
(173) (0) (41) (80)
(3) (6) (6) (15)
High
0 0 0 0
(0) (0) (0) (0)
(11) (6) (2) (19)
Total
15 0 11 9
(66) (0) (38) (43)
(40) (40) (80) (160)
Source: Household Survey.
67
Annexure Table – 5.8
Economic Valuation of Crabs and Shrimps Marketed (on Site) across Income Categories
Income Levels
Talukas Total
Keti Bunder Kharo Chhan Shah Bunder
Crabs Shrimps Crabs Shrimps Crabs Shrimps Crabs Shrimps
Subsistence
500 1030 1781 3431 1976 4526 1678 3652
(1581) (1683) (2646) (5692) (3874) (8596) (3293) (7184)
(10) (10) (16) (16) (34) (34) (60) (60)
Low
2731 15769 3167 6283 2382 13713 2609 12861
(2867) (29111) (3243) (6574) (5104) (35898) (4312) (30772)
(16) (16) (12) (12) (38) (38) (66) (66)
Middle
18333 26333 1450 18000 750 13000 4547 17667
(7638) (23029) (2477) (35553) (1837) (14283) (7921) (25010)
(3) (3) (6) (6) (6) (6) (15) (15)
High
9545 68500 5000 23333 1700 2450 7284 47284
(17558) (88175) (12247) (38297) (707) (1061) (14876) (73596)
(11) (11) (6) (6) (2) (2) (19) (19)
Total
5218 27378 2630 9458 2070 9474 2997 13946
(10608) (55296) (5209) (20823) (4345) (25859) (6734) (35343)
(40) (40) (40) (40) (80) (80) (160) (160)
Source: Household Survey.
Annexure Table – 5.9
Economic Valuation of Shell Fish across Income Categories
Income Levels Talukas
Total Keti Bunder Kharo Chhan Shah Bunder
Subsistence
300 844 412 508
(949) (1568) (1184) (1261)
(10) (16) (34) (60)
Low
875 2883 895 1252
(2527) (3355) (2699) (2851)
(16) (12) (38) (66)
Middle
0 667 0 267
(0) (1633) (0) (1033)
(3) (6) (6) (15)
High
36364 0 0 21053
(120605) (0) (0) (91766)
(11) (6) (2) (19)
Total
10425 1303 600 3232
(63199) (2375) (2023) (31631)
(40) (40) (80) (160)
Source: Household Survey.
68
Annexure Table – 5.13
Economic Valuation of Benefits Marketed and Non-Marketed across Income Categories
Income Levels
Keti Bunder Kharo Chhan Shah Bunder Total
Non-Marketed
Marketed Non-
Marketed Marketed
Non-Marketed
Marketed Non-
Marketed Marketed
Subsistence
2090 1610 947 2131 903 6894 1113 4743
(3489) (2420) (1410) (3343) (1263) (17703) (1857) (13609)
(10) (10) (16) (16) (34) (34) (60) (60)
Low
3094 6744 2283 164400 1508 9421 2033 36950
(2607) (6455) (1600) (546614) (1549) (17135) (1954) (233253)
(16) (16) (12) (12) (38) (38) (66) (66)
Middle
1300 6667 2567 11400 2350 7333 2227 8827
(954) (11547) (2221) (15435) (2870) (7448) (2253) (11346)
(3) (3) (6) (6) (6) (6) (15) (15)
High
7473 95636 4667 76667 3000 4200 6116 80021
(6180) (119989) (4367) (114310) (1131) (566) (5430) (111444)
(11) (11) (6) (6) (2) (2) (19) (19)
Total
3913 29900 2149 63382 1351 8060 2191 27351
(4526) (73494) (2483) (301836) (1603) (16548) (2986) (155958)
(40) (40) (40) (40) (80) (80) (160) (160)
Source: Household Survey.
69
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